This document summarizes an approach for image-based information retrieval using deep learning and clustering techniques. It begins by discussing how current search engines rely on text-based approaches that have limitations. The proposed approach uses deep learning to extract visual features from images and hierarchical clustering to organize similar images. Images are initially retrieved based on a user query, then re-ranked based on computed relevance scores to return more relevant results. The approach was found to reduce the semantic gap compared to text-based methods by leveraging visual features from images.
Image Search by using various Reranking MethodsIRJET Journal
This document discusses various image reranking methods that can be used to improve image search results. It provides an overview of different reranking approaches such as clustering-based methods, classification-based methods, and graph-based methods. For each category, several specific reranking techniques are described and their advantages and limitations are discussed. The purpose of the document is to review existing image reranking methods and provide a comparative analysis to help researchers develop more effective image search systems.
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This document proposes a social re-ranking system for tag-based image retrieval from social media datasets. It first retrieves images based on keyword matching of the query tags. It then applies three re-ranking steps: 1) Inter-user ranking to rank images by user contributions to the query, 2) Time stamp ranking to prioritize more recent images based on title and timestamp, 3) View ranking to improve relevance by considering image view counts. An experiment on a social image dataset showed the method effectively and efficiently retrieves more relevant and diverse images compared to other tag-based image ranking methods.
This document proposes a content-based image search engine that can retrieve relevant images from a large database based on a user-input query image. It discusses how content-based image retrieval systems work by extracting visual features like color, texture and shape from images. The proposed search engine would detect faces in input images using OpenCV and compare visual features to find matching images in the database. It would then retrieve and display the related information and images to the user. The goal is to build a more accurate image search compared to traditional text-based search engines by analyzing visual content of images.
Adaptive Search Based On User Tags in Social NetworkingIOSR Journals
This document summarizes an article about adaptive search based on user tags in social networking. It discusses using tags that users apply to images in social media sites like Flickr to improve image search and personalize results. It proposes using topic models to identify different meanings of ambiguous tags and a user's interests to display more relevant images. The framework involves reranking images based on aesthetics scores predicted from user comments, and using tag-based and group-based metadata to discover topics and personalize search results. Future work could further analyze community-generated metadata to identify interests and refine search algorithms.
IRJET- Image Seeker:Finding Similar ImagesIRJET Journal
This document describes Image Seeker, an image retrieval system that allows users to search for similar images by inputting a query image. Image Seeker uses shape context and SIFT descriptors to represent and match images. It compresses image representations using deep autoencoding to greatly improve storage and search efficiency. To rank search results, Image Seeker semantically interprets the query image and performs median filtering on the distance of retrieved images from the query. Image Seeker was developed to enable searching large image collections in applications like trademarks, art galleries, retail, fashion, interior design, and law enforcement.
A soft computing approach for image searching using visual rerankingIAEME Publication
The document discusses image search and ranking techniques. It describes how current search engines primarily use text-based retrieval, which can return many irrelevant images. The document then proposes a visual reranking approach to re-order images based on visual similarity analysis to improve search results. Key aspects of the approach include extracting image features, analyzing visual similarities between images, and leveraging these similarities to provide a reranked output with more relevant images prioritized.
A Review on User Personalized Tag Based Image Search by Tag RelevanceIRJET Journal
This document reviews approaches for user personalized tag-based image search. It discusses how tag-based image retrieval (TBIR) uses manually assigned tags to represent and search for images, as opposed to content-based image retrieval (CBIR) which matches images based on visual similarity. The document proposes a system that combines TBIR with CBIR, using both semantic tags and visual features to rank images for a user. It also discusses using clustering, common tags, and user profiles to filter images during the retrieval process. Experimental results showed that incorporating semantic and visual information improves diversity in the retrieved results compared to tag-based retrieval alone.
Image Search by using various Reranking MethodsIRJET Journal
This document discusses various image reranking methods that can be used to improve image search results. It provides an overview of different reranking approaches such as clustering-based methods, classification-based methods, and graph-based methods. For each category, several specific reranking techniques are described and their advantages and limitations are discussed. The purpose of the document is to review existing image reranking methods and provide a comparative analysis to help researchers develop more effective image search systems.
Social Re-Ranking using Tag Based Image SearchIRJET Journal
This document proposes a social re-ranking system for tag-based image retrieval from social media datasets. It first retrieves images based on keyword matching of the query tags. It then applies three re-ranking steps: 1) Inter-user ranking to rank images by user contributions to the query, 2) Time stamp ranking to prioritize more recent images based on title and timestamp, 3) View ranking to improve relevance by considering image view counts. An experiment on a social image dataset showed the method effectively and efficiently retrieves more relevant and diverse images compared to other tag-based image ranking methods.
This document proposes a content-based image search engine that can retrieve relevant images from a large database based on a user-input query image. It discusses how content-based image retrieval systems work by extracting visual features like color, texture and shape from images. The proposed search engine would detect faces in input images using OpenCV and compare visual features to find matching images in the database. It would then retrieve and display the related information and images to the user. The goal is to build a more accurate image search compared to traditional text-based search engines by analyzing visual content of images.
Adaptive Search Based On User Tags in Social NetworkingIOSR Journals
This document summarizes an article about adaptive search based on user tags in social networking. It discusses using tags that users apply to images in social media sites like Flickr to improve image search and personalize results. It proposes using topic models to identify different meanings of ambiguous tags and a user's interests to display more relevant images. The framework involves reranking images based on aesthetics scores predicted from user comments, and using tag-based and group-based metadata to discover topics and personalize search results. Future work could further analyze community-generated metadata to identify interests and refine search algorithms.
IRJET- Image Seeker:Finding Similar ImagesIRJET Journal
This document describes Image Seeker, an image retrieval system that allows users to search for similar images by inputting a query image. Image Seeker uses shape context and SIFT descriptors to represent and match images. It compresses image representations using deep autoencoding to greatly improve storage and search efficiency. To rank search results, Image Seeker semantically interprets the query image and performs median filtering on the distance of retrieved images from the query. Image Seeker was developed to enable searching large image collections in applications like trademarks, art galleries, retail, fashion, interior design, and law enforcement.
A soft computing approach for image searching using visual rerankingIAEME Publication
The document discusses image search and ranking techniques. It describes how current search engines primarily use text-based retrieval, which can return many irrelevant images. The document then proposes a visual reranking approach to re-order images based on visual similarity analysis to improve search results. Key aspects of the approach include extracting image features, analyzing visual similarities between images, and leveraging these similarities to provide a reranked output with more relevant images prioritized.
A Review on User Personalized Tag Based Image Search by Tag RelevanceIRJET Journal
This document reviews approaches for user personalized tag-based image search. It discusses how tag-based image retrieval (TBIR) uses manually assigned tags to represent and search for images, as opposed to content-based image retrieval (CBIR) which matches images based on visual similarity. The document proposes a system that combines TBIR with CBIR, using both semantic tags and visual features to rank images for a user. It also discusses using clustering, common tags, and user profiles to filter images during the retrieval process. Experimental results showed that incorporating semantic and visual information improves diversity in the retrieved results compared to tag-based retrieval alone.
IRJET-A Review on User Personalized Tag Based Image Search by Tag RelevanceIRJET Journal
This document reviews approaches for user personalized tag-based image search. It discusses how tag-based image retrieval (TBIR) uses manually assigned tags to represent images, as opposed to content-based image retrieval (CBIR) which matches images based on visual similarity. The paper proposes a system that combines TBIR with CBIR, using semantic and visual features to re-rank images for improved results. It also discusses using social media image tagging and geo-tagging techniques to better organize large image collections for search. The system architecture incorporates tagging, clustering, indexing and both online and offline components to perform user personalized tag-based image search.
This document summarizes an article that proposes a new approach to improving image web search techniques. It begins with an abstract that describes how rapidly increasing internet users and multimedia search are increasing network traffic, with most traffic being for searching multimedia content online. It then provides background on existing issues with image search and commonly used algorithms. The document proposes a hybrid image search engine that searches by image-to-image comparison, text/keywords, and uses a hybrid matches graph and time sensitivity filter to improve results. It describes the training and testing phases, featuring feature extraction and annotation matching to retrieve relevant images from queries.
This document describes a proposed content-based image retrieval system that uses histogram values and user feedback to effectively search and rank image search results. The proposed system tracks user navigation patterns and stores user feedback information separately from image data to improve search performance. Images are ranked based on their histogram values, user feedback, text metadata, and number of clicks to better capture user intent than existing keyword-based search systems. This approach aims to address challenges with existing CBIR systems such as helping users refine image queries and reducing information overload through improved query understanding and result ranking.
IRJET-Semi-Supervised Collaborative Image Retrieval using Relevance FeedbackIRJET Journal
This document describes a semi-supervised collaborative image retrieval system using relevance feedback. The system aims to improve the performance of content-based image retrieval (CBIR) systems by reducing the number of images a user must label during relevance feedback. It uses a semi-supervised approach where the user only needs to label a few of the most informative images. These labeled images are used to train a support vector machine (SVM) classifier. The images in the database are then resorted based on a new similarity metric determined by the classifier. The system provides iteratively improved retrieval results until the user is satisfied, thereby bridging the semantic gap between low-level visual features and high-level semantics.
ENHANCED WEB IMAGE RE-RANKING USING SEMANTIC SIGNATURESIAEME Publication
Several commercial search engines adopt Image re- ranking approach to enhance the quality of results for web based image search .When an user issues a query keyword, the search engine first selects a group of images based on textual information. If the user selects a query image from the retrieved group, the rest of the images are re-ranked based on their visual similarities with the query image. The images with similar visual features cannot be correlated. Also learning a universal visual semantic space which depicts the characteristics of images which are highly different to each other is a tedious task.
IRJET- Text-based Domain and Image Categorization of Google Search Engine usi...IRJET Journal
This document discusses a proposed system for categorizing search engine results using conceptual clustering. The system analyzes the content of search results to extract relevant concepts, then uses a personalized conceptual clustering algorithm to generate a decision tree of query clusters. This tree can be used to identify categories for web pages and provide topically relevant results to users. The system aims to improve on traditional ranked search results by categorizing results based on the conceptual preferences and interests of individual users.
A Survey on Image retrieval techniques with feature extractionIRJET Journal
This document discusses content-based image retrieval techniques. It provides an overview of different image retrieval approaches, including text-based, content-based, and hybrid methods. Content-based image retrieval aims to retrieve images based on automatically extracted visual features like color, texture, and shape, rather than relying on textual metadata or keywords. The document reviews recent research that has improved content-based image retrieval performance, such as incorporating relevance feedback and focusing on local image regions rather than global features. It also proposes a new image retrieval model to further optimize existing techniques.
A NOVEL WEB IMAGE RE-RANKING APPROACH BASED ON QUERY SPECIFIC SEMANTIC SIGNAT...Journal For Research
Image re-ranking, is an effective way to improve the results of web-based image search. Given a query keyword, a pool of images are initailly retrieved primarily based on textual data, the remaining images are re-ranked based on their visual similarities with the query image corresponding to the user input. A major challenge is that the similarities of visual features don't well correlate with images’ semantic meanings that interpret users’ search intention. Recently people proposed to match pictures in a semantic space that used attributes or reference categories closely associated with the semantic meanings of images as basis. Even though, learning a universal visual semantic space to characterize extremely diverse images from the internet is troublesome and inefficient. In this thesis, we propose a completely distinctive image re-ranking framework that learns completely different semantic spaces for numerous query keywords automatically at the on-line stage. The visual features of images are projected into their corresponding semantic spaces to induce semantic signatures. At the online stage, images are re-ranked by scrutiny their semantic signatures obtained from the semantic spaces such that by the query keyword. The proposed query-specific semantic signatures considerably improve both the accuracy and efficiency of image re-ranking.
A Graph-based Web Image Annotation for Large Scale Image RetrievalIRJET Journal
1) The document proposes a graph-based framework called Web Image Annotation for Large Scale Image Retrieval to improve the accuracy of automatic image annotation.
2) The framework first identifies a set of visually similar images from a large image database to label a query image, then applies a graph pattern matching algorithm to find representative keywords from the annotations of similar images.
3) The approach is extended to Probabilistic Reverse Annotation to rank relevant images, which takes the novel approach of matching keywords to images rather than images to keywords to improve annotation performance for large datasets.
IRJET- A Novel Technique for Inferring User Search using Feedback SessionsIRJET Journal
This document proposes a novel technique to infer user search goals using feedback sessions. It aims to address limitations in existing approaches like noisy search results, small numbers of clicked URLs, and lack of consideration of user feedback. The proposed approach generates feedback sessions from user click logs, pre-processes the data, extracts keywords from restructured results, re-ranks the results based on keywords and user history, and categorizes the re-ranked results using predefined categories. The technique is evaluated using Average Precision, which compares it to other clustering and classification algorithms. The goal is to improve information retrieval by better representing user search interests and needs.
FACE EXPRESSION IDENTIFICATION USING IMAGE FEATURE CLUSTRING AND QUERY SCHEME...Editor IJMTER
Web mining techniques are used to analyze the web page contents and usage details. Human facial
images are shared in the internet and tagged with additional information. Auto face annotation techniques are used
to annotate facial images automatically. Annotations are used in online photo search and management.
Classification techniques are used to assign the facial annotation. Supervised or semi-supervised machine learning
techniques are used to train the classification models. Facial images with labels are used in the training process.
Noisy and incomplete labels are referred as weak labels. Search-based face annotation (SBFA) is assigned by
mining weakly labeled facial images available on the World Wide Web (WWW). Unsupervised label refinement
(ULR) approach is used for refining the labels of web facial images with machine learning techniques. ULR
scheme is used to enhance the label quality using graph-based and low-rank learning approach. The training phase
is designed with facial image collection, facial feature extraction, feature indexing and label refinement learning
steps. Similar face retrieval and voting based face annotation tasks are carried out under the testing phase.
Clustering-Based Approximation (CBA) algorithm is applied to improve the scalability. Bisecting K-means
clustering based algorithm (BCBA) and divisive clustering based algorithm (DCBA) are used to group up the
facial images. Multi step Gradient Algorithm is used for label refinement process. The web face annotation scheme
is enhanced to improve the label quality with low refinement overhead. Noise reduction is method is integrated
with the label refinement process. Duplicate name removal process is integrated with the system. The indexing
scheme is enhanced with weight values for the labels. Social contextual information is used to manage the query
facial image relevancy issues.
Nowadays Social Media focus on users to billions of images, famous e commerce web sites such as Flipkart, Amazon etc. Tag-primarily based definitely image are seeking for is an essential method to find photos shared with the aid of manner of clients in social networks. But, a manner to make the top ranked result applicable and with range is difficult. In this paper, we advocate a topic diverse ranking method for tag-primarily based photo retrieval with the eye of selling the situation insurance overall performance. First, we bring together a tag graph based totally absolutely at the similarity among every tag. Then network detection approach is accomplished to mine the subject community of every tag. After that, inter-community and intra-network ranking are added to gather the very last retrieved results. Inside the inter-network rating way, an adaptive random stroll model is employed to rank the network primarily based at the multi-information of every topic community D. Dhayalan | M. Queen Mary Vidya | B. Gowri Priya "Image Tagging With Social Assistance" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Active Galaxy , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd14566.pdf
http://www.ijtsrd.com/engineering/computer-engineering/14566/image-tagging-with-social-assistance/d-dhayalan
IRJET - Re-Ranking of Google Search ResultsIRJET Journal
This document summarizes a research paper that proposes a hybrid personalized re-ranking approach to search results. It models a user's search interests using a conceptual user profile containing categories and concepts extracted from clicked results and a concept hierarchy. The user profile contains two types of documents - taxonomy documents representing general interests and viewed documents representing specific interests. A hybrid re-ranking process then semantically integrates the user's general and specific interests from their profile with search engine rankings to improve result relevance.
Face Annotation using Co-Relation based Matching for Improving Image Mining ...IRJET Journal
This document discusses face annotation techniques for improving image mining in videos. It begins by introducing the need for better image retrieval with the rise of online sharing. It then discusses challenges with face annotation in videos and existing techniques like content-based image retrieval and search-based face annotation. The document analyzes limitations of these existing techniques, such as semantic gaps with manual tagging, decreased accuracy, and poor generalization with new data. It proposes using correlation-based matching to address problems in face recognition techniques.
Query- And User-Dependent Approach for Ranking Query Results in Web DatabasesIOSR Journals
This document presents a new approach for ranking query results from web databases called Query and User Dependent Ranking. The approach considers two aspects: query similarity, which accounts for different users having similar queries, and user similarity, which accounts for different queries having similar user preferences. A prototype application was built to test the model. Empirical results found the approach to be efficient and suitable for real-world applications. The approach uses a workload file that is updated with ranking functions as new queries are made to track user and query similarities over time.
Structured data and metadata evaluation methodology for organizations looking...Emily Kolvitz
This research proposal outlines a methodology for evaluating an organization's use of structured data and metadata to improve the findability of images on the web. The methodology involves assessing an organization's file naming conventions, use of alt text, embedded metadata, schema.org markup and more. It also involves analyzing search engine results and structured data validation tools. The goal is to establish a baseline of an organization's current practices and identify areas for improvement to maintain online relevancy. The expected outcomes include a benchmark for an organization's structured data maturity and a roadmap for improving image findability on and off their website.
This paper presents a method based on principle of content based image retrieval for online shopping based on color, HSV aiming at efficient retrieval of images from the large database for online shopping specially for fashion shopping. Here, HSV modeling is used for creating our application with a huge image database, which compares image source with the destination components. In this paper, a technique is used for finding items by image search, which is convenient for buyers in order to allow them to see the products. The reason for using image search for items instead of text searches is that item searching by keywords or text has some issues such as errors in search items, expansion in search and inaccuracy in search results. This paper is an attempt to help users to choose the best options among many products and decide exactly what they want with the fast and easy search by image retrieval. This technology is providing a new search mode, searching by image, which will help buyers for finding the same or similar image retrieval in the database store. The image searching results have been made customers buy products quickly. This feature is implemented to identify and extract features of prominent object present in an image. Using different statistical measures, similarity measures are calculated and evaluated. Image retrieval based on color is a trivial task. Identifying objects of prominence in an image and retrieving image with similar features is a complex task. Finding prominent object in an image is difficult in a background image and is the challenging task in retrieving images. We calculated and change the region of interest in order to increase speed of operation as well as accuracy by masking the background content. The Implementation results proved that proposed method is effective in recalling the images of same pattern or texture.
JPD1436 Web Image Re-Ranking Using Query-Specific Semantic Signatureschennaijp
We have best 2014 free dot not projects topics are available along with all document, you can easy to find out number of documents for various projects titles.
For More Details:
http://jpinfotech.org/final-year-ieee-projects/2014-ieee-projects/dot-net-projects/
Projection Multi Scale Hashing Keyword Search in Multidimensional DatasetsIRJET Journal
The document discusses a novel method called ProMiSH (Projection and Multi Scale Hashing) for keyword search in multi-dimensional datasets. ProMiSH uses random projection and hash-based index structures to achieve high scalability and speedup of more than four orders over state-of-the-art tree-based techniques. Empirical studies on real and synthetic datasets of sizes up to 10 million objects and 100 dimensions show ProMiSH scales linearly with dataset size, dimension, query size, and result size. The method groups objects embedded in a vector space that are tagged with keywords matching a given query.
IRJET- Popularity based Recommender Sytsem for Google MapsIRJET Journal
This document describes a popularity-based recommender system for Google Maps that provides location recommendations to users based on their preferences and past visits. It uses machine learning algorithms like collaborative filtering to analyze user data and recommend popular places around a user's current location. The system aims to reduce information overload by learning from a user's profile and past actions to suggest new and interesting nearby locations like restaurants, parks, museums etc. based on what similar users enjoyed. It describes the framework, which collects a user's ratings for different places through a questionnaire, calculates ratings, predicts suitable places and provides recommendations on Google Maps. The goal is to accurately recommend locations tailored to each user's interests.
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
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Web mining techniques are used to analyze the web page contents and usage details. Human facial
images are shared in the internet and tagged with additional information. Auto face annotation techniques are used
to annotate facial images automatically. Annotations are used in online photo search and management.
Classification techniques are used to assign the facial annotation. Supervised or semi-supervised machine learning
techniques are used to train the classification models. Facial images with labels are used in the training process.
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mining weakly labeled facial images available on the World Wide Web (WWW). Unsupervised label refinement
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facial images. Multi step Gradient Algorithm is used for label refinement process. The web face annotation scheme
is enhanced to improve the label quality with low refinement overhead. Noise reduction is method is integrated
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scheme is enhanced with weight values for the labels. Social contextual information is used to manage the query
facial image relevancy issues.
Nowadays Social Media focus on users to billions of images, famous e commerce web sites such as Flipkart, Amazon etc. Tag-primarily based definitely image are seeking for is an essential method to find photos shared with the aid of manner of clients in social networks. But, a manner to make the top ranked result applicable and with range is difficult. In this paper, we advocate a topic diverse ranking method for tag-primarily based photo retrieval with the eye of selling the situation insurance overall performance. First, we bring together a tag graph based totally absolutely at the similarity among every tag. Then network detection approach is accomplished to mine the subject community of every tag. After that, inter-community and intra-network ranking are added to gather the very last retrieved results. Inside the inter-network rating way, an adaptive random stroll model is employed to rank the network primarily based at the multi-information of every topic community D. Dhayalan | M. Queen Mary Vidya | B. Gowri Priya "Image Tagging With Social Assistance" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Active Galaxy , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd14566.pdf
http://www.ijtsrd.com/engineering/computer-engineering/14566/image-tagging-with-social-assistance/d-dhayalan
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Face Annotation using Co-Relation based Matching for Improving Image Mining ...IRJET Journal
This document discusses face annotation techniques for improving image mining in videos. It begins by introducing the need for better image retrieval with the rise of online sharing. It then discusses challenges with face annotation in videos and existing techniques like content-based image retrieval and search-based face annotation. The document analyzes limitations of these existing techniques, such as semantic gaps with manual tagging, decreased accuracy, and poor generalization with new data. It proposes using correlation-based matching to address problems in face recognition techniques.
Query- And User-Dependent Approach for Ranking Query Results in Web DatabasesIOSR Journals
This document presents a new approach for ranking query results from web databases called Query and User Dependent Ranking. The approach considers two aspects: query similarity, which accounts for different users having similar queries, and user similarity, which accounts for different queries having similar user preferences. A prototype application was built to test the model. Empirical results found the approach to be efficient and suitable for real-world applications. The approach uses a workload file that is updated with ranking functions as new queries are made to track user and query similarities over time.
Structured data and metadata evaluation methodology for organizations looking...Emily Kolvitz
This research proposal outlines a methodology for evaluating an organization's use of structured data and metadata to improve the findability of images on the web. The methodology involves assessing an organization's file naming conventions, use of alt text, embedded metadata, schema.org markup and more. It also involves analyzing search engine results and structured data validation tools. The goal is to establish a baseline of an organization's current practices and identify areas for improvement to maintain online relevancy. The expected outcomes include a benchmark for an organization's structured data maturity and a roadmap for improving image findability on and off their website.
This paper presents a method based on principle of content based image retrieval for online shopping based on color, HSV aiming at efficient retrieval of images from the large database for online shopping specially for fashion shopping. Here, HSV modeling is used for creating our application with a huge image database, which compares image source with the destination components. In this paper, a technique is used for finding items by image search, which is convenient for buyers in order to allow them to see the products. The reason for using image search for items instead of text searches is that item searching by keywords or text has some issues such as errors in search items, expansion in search and inaccuracy in search results. This paper is an attempt to help users to choose the best options among many products and decide exactly what they want with the fast and easy search by image retrieval. This technology is providing a new search mode, searching by image, which will help buyers for finding the same or similar image retrieval in the database store. The image searching results have been made customers buy products quickly. This feature is implemented to identify and extract features of prominent object present in an image. Using different statistical measures, similarity measures are calculated and evaluated. Image retrieval based on color is a trivial task. Identifying objects of prominence in an image and retrieving image with similar features is a complex task. Finding prominent object in an image is difficult in a background image and is the challenging task in retrieving images. We calculated and change the region of interest in order to increase speed of operation as well as accuracy by masking the background content. The Implementation results proved that proposed method is effective in recalling the images of same pattern or texture.
JPD1436 Web Image Re-Ranking Using Query-Specific Semantic Signatureschennaijp
We have best 2014 free dot not projects topics are available along with all document, you can easy to find out number of documents for various projects titles.
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Projection Multi Scale Hashing Keyword Search in Multidimensional DatasetsIRJET Journal
The document discusses a novel method called ProMiSH (Projection and Multi Scale Hashing) for keyword search in multi-dimensional datasets. ProMiSH uses random projection and hash-based index structures to achieve high scalability and speedup of more than four orders over state-of-the-art tree-based techniques. Empirical studies on real and synthetic datasets of sizes up to 10 million objects and 100 dimensions show ProMiSH scales linearly with dataset size, dimension, query size, and result size. The method groups objects embedded in a vector space that are tagged with keywords matching a given query.
IRJET- Popularity based Recommender Sytsem for Google MapsIRJET Journal
This document describes a popularity-based recommender system for Google Maps that provides location recommendations to users based on their preferences and past visits. It uses machine learning algorithms like collaborative filtering to analyze user data and recommend popular places around a user's current location. The system aims to reduce information overload by learning from a user's profile and past actions to suggest new and interesting nearby locations like restaurants, parks, museums etc. based on what similar users enjoyed. It describes the framework, which collects a user's ratings for different places through a questionnaire, calculates ratings, predicts suitable places and provides recommendations on Google Maps. The goal is to accurately recommend locations tailored to each user's interests.
Similar to Image Based Information Retrieval Using Deep Learning and Clustering Techniques (20)
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
This study compares the use of Stark Steel and TMT Steel as reinforcement materials in a two-way reinforced concrete slab. Mechanical testing is conducted to determine the tensile strength, yield strength, and other properties of each material. A two-way slab design adhering to codes and standards is executed with both materials. The performance is analyzed in terms of deflection, stability under loads, and displacement. Cost analyses accounting for material, durability, maintenance, and life cycle costs are also conducted. The findings provide insights into the economic and structural implications of each material for reinforcement selection and recommendations on the most suitable material based on the analysis.
Effect of Camber and Angles of Attack on Airfoil CharacteristicsIRJET Journal
This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
This document reviews the progress and challenges of aluminum-based metal matrix composites (MMCs), focusing on their fabrication processes and applications. It discusses how various aluminum MMCs have been developed using reinforcements like borides, carbides, oxides, and nitrides to improve mechanical and wear properties. These composites have gained prominence for their lightweight, high-strength and corrosion resistance properties. The document also examines recent advancements in fabrication techniques for aluminum MMCs and their growing applications in industries such as aerospace and automotive. However, it notes that challenges remain around issues like improper mixing of reinforcements and reducing reinforcement agglomeration.
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
artificial intelligence and data science contents.pptxGauravCar
What is artificial intelligence? Artificial intelligence is the ability of a computer or computer-controlled robot to perform tasks that are commonly associated with the intellectual processes characteristic of humans, such as the ability to reason.
› ...
Artificial intelligence (AI) | Definitio
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...shadow0702a
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.