Presented at Color Imaging XVIII: Displaying, Processing, Hardcopy, and Applications in 2013. Application of machine color naming to 200,000+ wikipedia images.
This is the basic introductory presentation for beginners. It gives you the idea about what is image processing means. The presentation consists of introduction to digital image processing, image enhancement, image filtering, finding an image edge, image analysis, tools for image processing and finally some application of digital image processing.
Lec-17: Sparse Signal Processing & Applications [notes]
Sparse signal processing, recovery of sparse signal via L1 minimization. Applications including face recognition, coupled dictionary learning for image super-resolution.
This document provides information about a digital image processing lecture given by Dr. Moe Moe Myint from Technological University in Kyaukse, Myanmar. It includes the lecture schedule and contact information for Dr. Myint. The document also provides an overview of Chapter 2 which discusses elements of visual perception, light and the electromagnetic spectrum, image sensing and acquisition, image sampling and quantization, and basic relationships between pixels. It provides examples of different types of digital images including intensity, RGB, binary, and index images. It also discusses the effects of spatial and intensity level resolution on images.
WEBINAR ON FUNDAMENTALS OF DIGITAL IMAGE PROCESSING DURING COVID LOCK DOWN by K.Vijay Anand , Associate Professor, Department of Electronics and Instrumentation Engineering , R.M.K Engineering College, Tamil Nadu , India
There are several types of images, including binary, grayscale, and color images. Binary images contain only two values (0 and 1) representing black and white pixels with no gray levels. Grayscale images use integer values from 0-255 to represent pixel intensity from black to white. Color images can be "true color" storing RGB pixel values, or "indexed color" where pixels reference a color map for a reduced set of colors.
1. The document discusses various topics related to digital image representation and processing. It describes how images are digitized through sampling and quantization.
2. Pixel values, image resolution, file formats for storing images like JPEG and GIF are explained. Techniques for image editing like selection tools, painting tools, layers and blending are also covered.
3. The document provides an overview of important concepts in digital image representation and processing including how images are digitized and stored as digital data, techniques for editing images, and methods for manipulating pixels within an image.
This is the basic introductory presentation for beginners. It gives you the idea about what is image processing means. The presentation consists of introduction to digital image processing, image enhancement, image filtering, finding an image edge, image analysis, tools for image processing and finally some application of digital image processing.
Lec-17: Sparse Signal Processing & Applications [notes]
Sparse signal processing, recovery of sparse signal via L1 minimization. Applications including face recognition, coupled dictionary learning for image super-resolution.
This document provides information about a digital image processing lecture given by Dr. Moe Moe Myint from Technological University in Kyaukse, Myanmar. It includes the lecture schedule and contact information for Dr. Myint. The document also provides an overview of Chapter 2 which discusses elements of visual perception, light and the electromagnetic spectrum, image sensing and acquisition, image sampling and quantization, and basic relationships between pixels. It provides examples of different types of digital images including intensity, RGB, binary, and index images. It also discusses the effects of spatial and intensity level resolution on images.
WEBINAR ON FUNDAMENTALS OF DIGITAL IMAGE PROCESSING DURING COVID LOCK DOWN by K.Vijay Anand , Associate Professor, Department of Electronics and Instrumentation Engineering , R.M.K Engineering College, Tamil Nadu , India
There are several types of images, including binary, grayscale, and color images. Binary images contain only two values (0 and 1) representing black and white pixels with no gray levels. Grayscale images use integer values from 0-255 to represent pixel intensity from black to white. Color images can be "true color" storing RGB pixel values, or "indexed color" where pixels reference a color map for a reduced set of colors.
1. The document discusses various topics related to digital image representation and processing. It describes how images are digitized through sampling and quantization.
2. Pixel values, image resolution, file formats for storing images like JPEG and GIF are explained. Techniques for image editing like selection tools, painting tools, layers and blending are also covered.
3. The document provides an overview of important concepts in digital image representation and processing including how images are digitized and stored as digital data, techniques for editing images, and methods for manipulating pixels within an image.
This document provides an overview of the topics that will be covered in lectures 1-3 of the course MATHEMATICAL IMAGING TECHNIQUES. The lectures will cover fundamentals of image formation, sampling and quantization, spatial domain filtering techniques including intensity transformations, histogram equalization, and smoothing/sharpening filters. Frequency domain filtering including the Fourier transform and filters such as lowpass, highpass, and bandpass will also be discussed. Recommended textbooks and reference materials are provided.
Edge detection is one of the most powerful image analysis tools for enhancing and detecting edges. Indeed, identifying and localizing edges are a low level task in a variety of applications such as 3-D reconstruction, shape recognition, image compression, enhancement, and restoration. This paper introduces a new algorithm for detecting edges based on color space models. In this RGB image is taken as an input image and transforming the RGB image to color models such as YUV, YCbCr and XYZ. The edges have been detected for each component in color models separately and compared with the original image of that particular model. In order to measure the quality assessment between images, SSIM (Structural Similarity Index Method) and VIF (Visual Information Fidelity) has been calculated. The results have shown that XYZ color model is having high SSIM value and VIF value. In the previous papers, edge detection based on RGB color model has low SSIM and VIF values. So by converting the images into different color models shows a significant improvement in detection of edges. Keywords: Edge detection, Color models, SSIM, VIF.
This document describes a coin recognition system developed using MATLAB digital image processing techniques. It discusses two methods: a static image method where a single image is converted to binary, filled, and analyzed using edge detection and circle finding algorithms to identify coins. A video streaming method takes periodic screenshots, converts them, and compares measurements to a stored database to identify coins in real-time video. Key steps include image conversion, feature extraction using edge detection and circle finding, and measurement comparison to a stored database of coin images. The system is designed to maintain a consistent distance and angle between input images and the database images for accurate recognition.
This document discusses digital image processing using MATLAB. It begins by defining digital images and how they are represented by arrays of pixels in computer memory. It then discusses how images can be read into MATLAB and converted between color, grayscale, and binary representations. Various image processing operations are described such as edge detection, dilation, filling, and calculating region properties. Finally, examples are given of processing color images using intensity transformations and gamma correction.
Lec-07: Feature Aggregation and Image Retrieval System [notes]
Image retrieval system performance metrics, precision, recall, true positive rate, false positive rate; Bag of Words (BoW) and VLAD aggregation.
This document provides an overview of digital image processing. It discusses what digital image processing is, provides a brief history, and outlines some of the key stages involved, including image acquisition, enhancement, restoration, morphological processing, segmentation, representation and description, object recognition, and compression. It also discusses some example applications like medical imaging, autonomous vehicles, traffic monitoring, and biometrics. The document uses images to illustrate different concepts and stages in digital image processing.
This document discusses job design and outlines factors to consider when designing jobs for a pirate crew on a newly acquired ship. It identifies three types of task distribution - "foot soldier", "guardian", and "star" - based on the upside and downside risks of performance variance. When designing pirate crew jobs, one must account for necessity, strategy, skills availability, organizational issues, and resources, and consider what tasks are done, when and how, how many, in what order, and affecting factors, as well as task significance, autonomy, and feedback.
How to Play Well with Others (A Program on Dealing with Difficult People)Marian Madonia, CSP
Learn tips on how to deal with the most difficult people in your life. Nasty neighbor? Cranky customer? Prickly peer? Bossy Boss? Improve your communications skills and tap into listening tips that can help you get the edge!
A mother camel explains to her curious baby camel why camels have evolved certain physical traits that help them survive in the desert. The hump stores water, long legs help walk through sand, and thick eyelashes protect eyes from sand and wind. The baby camel realizes all these desert adaptations are useless at the zoo, learning that skills are only useful if used in the right context. The moral is about making sure to apply your abilities in an appropriate environment.
The document summarizes evidence-based strategies for effective teaching of reading. It discusses how struggling readers need to read more text to close gaps, and how interrupting students to correct mistakes during oral reading is not effective. It also outlines key instructional and infrastructural improvements from the Reading Next report, including direct comprehension instruction, instruction embedded in content areas, and extended time for literacy. Overall, the document promotes strategies to help all students read with meaning, joy, and increased volume.
Carolyne is a 17-year-old girl from Stoke-on-Trent, England who speaks Swahili as her native language. She enjoys communicating with friends on Facebook, listening to artists like Chris Brown, Michael Jackson, and Missy Elliot. Her favorite meal is chicken curry and she likes McDonald's fries. She finds Lamborghinis and convertibles to be cool cars and enjoys comedy and mildly scary movies.
El documento menciona varias obras maestras de la pintura del Renacimiento italiano, incluyendo pinturas de Fra Angelico, Piero della Francesca, Botticelli, Leonardo da Vinci, Miguel Ángel y Rafael, como La Anunciación, Federico de Montefeltro, La Primavera, El nacimiento de Venus, La Gioconda, el Techo de la Capilla Sixtina, El Juicio Final, La Sagrada Familia del Cordero y La escuela de Atenas.
This document discusses balanced literacy and collaborative teaching practices. It provides 6 elements of instruction that should be implemented for all students, which include ensuring every student reads texts they choose and understand, writes about personally meaningful topics, discusses reading and writing with peers, and listens to an adult read aloud. The document advocates for teachers to collaborate by sharing practices publicly and focusing on student learning outcomes. Effective collaboration requires an ongoing interactive process, capitalizing on different expertise to better meet diverse learner needs.
Destiny is a library catalog system that allows users to search for and check out books, videos, and other materials. The guide provides instructions for logging into Destiny using a user name and password. Once logged in, users can see items they have checked out, track previous searches, and create resource lists. The guide encourages exploring different search features and contacting library staff with any questions.
Redshift is a full-service market research consultancy established in 2007 in the UK. It aims to provide optimal market research designs and gain client trust and deliver value. Redshift's philosophy is to avoid cookie-cutter solutions and bring creativity to each project. It has expertise across various sectors and research methods. Redshift has access to over 7 million online panelists in 48 countries and can provide both qualitative and quantitative research techniques.
This document provides an overview of the topics that will be covered in lectures 1-3 of the course MATHEMATICAL IMAGING TECHNIQUES. The lectures will cover fundamentals of image formation, sampling and quantization, spatial domain filtering techniques including intensity transformations, histogram equalization, and smoothing/sharpening filters. Frequency domain filtering including the Fourier transform and filters such as lowpass, highpass, and bandpass will also be discussed. Recommended textbooks and reference materials are provided.
Edge detection is one of the most powerful image analysis tools for enhancing and detecting edges. Indeed, identifying and localizing edges are a low level task in a variety of applications such as 3-D reconstruction, shape recognition, image compression, enhancement, and restoration. This paper introduces a new algorithm for detecting edges based on color space models. In this RGB image is taken as an input image and transforming the RGB image to color models such as YUV, YCbCr and XYZ. The edges have been detected for each component in color models separately and compared with the original image of that particular model. In order to measure the quality assessment between images, SSIM (Structural Similarity Index Method) and VIF (Visual Information Fidelity) has been calculated. The results have shown that XYZ color model is having high SSIM value and VIF value. In the previous papers, edge detection based on RGB color model has low SSIM and VIF values. So by converting the images into different color models shows a significant improvement in detection of edges. Keywords: Edge detection, Color models, SSIM, VIF.
This document describes a coin recognition system developed using MATLAB digital image processing techniques. It discusses two methods: a static image method where a single image is converted to binary, filled, and analyzed using edge detection and circle finding algorithms to identify coins. A video streaming method takes periodic screenshots, converts them, and compares measurements to a stored database to identify coins in real-time video. Key steps include image conversion, feature extraction using edge detection and circle finding, and measurement comparison to a stored database of coin images. The system is designed to maintain a consistent distance and angle between input images and the database images for accurate recognition.
This document discusses digital image processing using MATLAB. It begins by defining digital images and how they are represented by arrays of pixels in computer memory. It then discusses how images can be read into MATLAB and converted between color, grayscale, and binary representations. Various image processing operations are described such as edge detection, dilation, filling, and calculating region properties. Finally, examples are given of processing color images using intensity transformations and gamma correction.
Lec-07: Feature Aggregation and Image Retrieval System [notes]
Image retrieval system performance metrics, precision, recall, true positive rate, false positive rate; Bag of Words (BoW) and VLAD aggregation.
This document provides an overview of digital image processing. It discusses what digital image processing is, provides a brief history, and outlines some of the key stages involved, including image acquisition, enhancement, restoration, morphological processing, segmentation, representation and description, object recognition, and compression. It also discusses some example applications like medical imaging, autonomous vehicles, traffic monitoring, and biometrics. The document uses images to illustrate different concepts and stages in digital image processing.
This document discusses job design and outlines factors to consider when designing jobs for a pirate crew on a newly acquired ship. It identifies three types of task distribution - "foot soldier", "guardian", and "star" - based on the upside and downside risks of performance variance. When designing pirate crew jobs, one must account for necessity, strategy, skills availability, organizational issues, and resources, and consider what tasks are done, when and how, how many, in what order, and affecting factors, as well as task significance, autonomy, and feedback.
How to Play Well with Others (A Program on Dealing with Difficult People)Marian Madonia, CSP
Learn tips on how to deal with the most difficult people in your life. Nasty neighbor? Cranky customer? Prickly peer? Bossy Boss? Improve your communications skills and tap into listening tips that can help you get the edge!
A mother camel explains to her curious baby camel why camels have evolved certain physical traits that help them survive in the desert. The hump stores water, long legs help walk through sand, and thick eyelashes protect eyes from sand and wind. The baby camel realizes all these desert adaptations are useless at the zoo, learning that skills are only useful if used in the right context. The moral is about making sure to apply your abilities in an appropriate environment.
The document summarizes evidence-based strategies for effective teaching of reading. It discusses how struggling readers need to read more text to close gaps, and how interrupting students to correct mistakes during oral reading is not effective. It also outlines key instructional and infrastructural improvements from the Reading Next report, including direct comprehension instruction, instruction embedded in content areas, and extended time for literacy. Overall, the document promotes strategies to help all students read with meaning, joy, and increased volume.
Carolyne is a 17-year-old girl from Stoke-on-Trent, England who speaks Swahili as her native language. She enjoys communicating with friends on Facebook, listening to artists like Chris Brown, Michael Jackson, and Missy Elliot. Her favorite meal is chicken curry and she likes McDonald's fries. She finds Lamborghinis and convertibles to be cool cars and enjoys comedy and mildly scary movies.
El documento menciona varias obras maestras de la pintura del Renacimiento italiano, incluyendo pinturas de Fra Angelico, Piero della Francesca, Botticelli, Leonardo da Vinci, Miguel Ángel y Rafael, como La Anunciación, Federico de Montefeltro, La Primavera, El nacimiento de Venus, La Gioconda, el Techo de la Capilla Sixtina, El Juicio Final, La Sagrada Familia del Cordero y La escuela de Atenas.
This document discusses balanced literacy and collaborative teaching practices. It provides 6 elements of instruction that should be implemented for all students, which include ensuring every student reads texts they choose and understand, writes about personally meaningful topics, discusses reading and writing with peers, and listens to an adult read aloud. The document advocates for teachers to collaborate by sharing practices publicly and focusing on student learning outcomes. Effective collaboration requires an ongoing interactive process, capitalizing on different expertise to better meet diverse learner needs.
Destiny is a library catalog system that allows users to search for and check out books, videos, and other materials. The guide provides instructions for logging into Destiny using a user name and password. Once logged in, users can see items they have checked out, track previous searches, and create resource lists. The guide encourages exploring different search features and contacting library staff with any questions.
Redshift is a full-service market research consultancy established in 2007 in the UK. It aims to provide optimal market research designs and gain client trust and deliver value. Redshift's philosophy is to avoid cookie-cutter solutions and bring creativity to each project. It has expertise across various sectors and research methods. Redshift has access to over 7 million online panelists in 48 countries and can provide both qualitative and quantitative research techniques.
Make a Wave - Branding Intro webinar - PatchworkPresentOgunte CIC
Our guest Olivia Knight, CEO of Patchwork Present on our latest Make a Wave Webinar went over all the crucial stuff that sums up your brand identity - your beliefs, your purpose, your product and what makes you different.
She encouraged the participants to "Not think too hard and stay succinct, really, really succinct.... and "Just be true, simple and human".
Here's the exercise she encouraged the Make a Wave fellows to go through, answering
WHY, WHO, then HOW and WHAT, about their business.
La Unión Europea ha acordado un paquete de sanciones contra Rusia por su invasión de Ucrania. Las sanciones incluyen restricciones a las importaciones de productos rusos de alta tecnología y a las exportaciones de bienes de lujo a Rusia. Además, se congelarán los activos de varios oligarcas rusos y se prohibirá el acceso de los bancos rusos a los mercados financieros de la UE.
This document discusses various issues that can occur in town settings such as raves, graffiti, smoking, drinking, drugs, violence perpetrated by chavs, yobs and gangsters.
The document discusses version control systems and their use. It describes how version control allows software developers on a team to work together and manage changes to source code over time. It provides examples of version control tools like Subversion, Mercurial and Git. It also outlines an exercise for students to set up an SVN repository on Google Code to practice using version control in groups.
The internship program involved 34 interns learning and applying user-centered design techniques to create 111 widgets for the Samsung Corby mobile phone. Through problem-based learning, field research, prototyping, and development, the interns completed the full user-centered design process. This resulted in a huge increase in widget downloads, with the interns' widgets representing 18% of all Samsung downloads after just two months. The internship demonstrated the value of involving users and of providing hands-on experience with user-centered design for young developers.
Vladimir Surin and Alexander Tyrsin - Research of properties of digital nois...AIST
The document discusses research into the properties of digital noise in contrast images. It finds that additive noise predominates in digital images and its formation has a non-linear character, leading to spreading of contrast boundaries. It compares the effectiveness of moving average, median, and generalized method of least absolute values (GMLAV) filters for smoothing noisy contrast images in an experiment. The results show that GMLAV filtering has significant advantages over averaging and median filtering for this task.
This document discusses image enhancement techniques in the spatial domain. It defines spatial domain processing as the direct manipulation of pixel values, as opposed to frequency domain processing which modifies the Fourier transform. The key techniques discussed are:
- Linear and non-linear transformations which map input pixel values to new output values.
- Spatial filters which operate on neighborhoods of pixels, including smoothing filters to reduce noise and sharpening filters to enhance edges.
- Histogram processing techniques like equalization to improve contrast in low contrast images.
The document provides examples of each technique and discusses their applications in image enhancement.
Projects on Digital Image Processing Research Thesis TopicsMatlab Simulation
The document describes several digital image processing projects that can be done using Matlab, including methods like hidden Markov models, weighted averaging, wavelets, and linear/nonlinear filtering. It also lists some common DIP modules like mass storage, image display, image sensors, and image processing hardware. Finally, it provides examples of uses for digital image processing like statistical analysis, biometrics, 3D graphics, multimedia, and visual content analysis.
Image Processing using Matlab . Useful for beginners to learn Image ProcessingAshok Kumar
Matlab can be used for image processing tasks such as loading, displaying, and manipulating images. Images are represented as matrices where each element corresponds to the pixel intensity values. Common operations include convolutions using various kernel filters to perform tasks like smoothing, sharpening, and edge detection. Functions such as imread, image, and imshow can load and display images. Built-in functions such as fspecial generate common kernel filters. Convolution functions convolve images with kernels to apply filtering effects.
3.point operation and histogram based image enhancementmukesh bhardwaj
The document discusses various techniques for digital image enhancement, including point operations, histogram equalization, and frequency domain methods. Point operations directly map input pixel values to output values using functions like contrast stretching and clipping. Histogram equalization maps values to equalize the image histogram for better contrast. Frequency methods like unsharp masking and homomorphic filtering enhance images in the frequency domain by modifying high and low frequency components. The techniques can be used to improve images for applications in digital photography, iris recognition, microscopy, and entertainment.
Digital Image Processing_ ch1 introduction-2003Malik obeisat
The document provides an introduction to digital image processing. It defines a digital image as a finite set of digital values representing a two-dimensional image. Digital image processing focuses on improving images for human interpretation and processing images for machine perception. The document outlines the history of digital image processing and provides examples of its use in applications such as image enhancement, medical imaging, satellite imagery, and industrial inspection. It also describes common stages in digital image processing like image acquisition, enhancement, restoration, segmentation, and compression.
The document discusses image processing and provides information on several key topics:
1. Image processing can be grouped into compression, preprocessing, and analysis. Preprocessing improves image quality by reducing noise and enhancing edges. Analysis extracts numeric or graphical information for tasks like classification.
2. Images are 2D matrices of intensity values represented by pixels. Common digital formats include grayscale, RGB, and RGBA. Higher bit depths allow more intensity levels to be represented.
3. Basic measurements of images include spatial resolution in pixels per unit, bit depth determining representable intensity levels, and factors like saturation and noise.
Panel Discussion. Alfred Borden
Principal, The Lighting Practice; Naomi Miller
Senior Lighting Engineer, Pacific Northwest National Laboratory; Willem Sillevis Smitt,- Xicato; Kevin Willmorth, Lumenique LLC
This document outlines the course syllabus for Digital Image Processing (DIP). It includes 5 units covering key topics in DIP like digital image fundamentals, image enhancement, restoration and segmentation, wavelets and compression, and image representation and recognition. The syllabus allocates 45 class periods to cover these units in depth. Recommended textbooks and references for the course are also provided.
The document describes the Colour Imaging Lab at the University of Granada in Spain. The lab conducts research in areas related to color vision, color images, color constancy, and using RGB cameras to recover spectral information. It has permanent staff and PhD students. It has published papers in international journals and conferences and worked on projects funded by the Spanish and Andalusian governments and private companies. The lab has various instruments including tunable liquid crystal filters, cameras, spectroradiometers, and a 3D scanner. It also teaches courses and hosts international students and thesis students.
introduction to Digital Image Processingnikesh gadare
The document provides an overview of the key concepts and stages involved in digital image processing. It discusses image acquisition, preprocessing such as enhancement and restoration, and post-processing which includes tasks like segmentation, description and recognition. The goal is to introduce fundamental concepts and classical methods of digital image processing. Various applications are also highlighted including medical imaging, surveillance, and industrial inspection.
Similar to Color naming 65,274,705,768 pixels (14)
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
1. Color naming 65,274,705,768 pixels
Nathan Moroney and Giordano Beretta
HP Labs
Electronic Imaging 2013: Color Imaging XVIII
2. Outline
Motivation
More (pixel) data
Finding and processing 65 billion pixels
Hint: Wikipedia & a dual core Open MP color namer
What did you learn?
The most frequent non-achromatic color term is…
What’s next?
Other than a trillion pixels
Electronic Imaging 2013: Color Imaging XVIII
3. Motivation
Previous work in crowd-sourcing color training data
and experimental efforts
Related work in the area of big (image) data
A. Torralba, R. Fergus, W. T. Freeman, "80 million tiny images: a
large dataset for non-parametric object and scene recognition",
IEEE Transactions on Pattern Analysis and Machine Intelligence,
vol.30(11), pp. 1958-1970, 2008.
Ben Shneiderman, "Extreme Visualization: Squeezing a Billion
Records into a Million Pixels", SIGMOD Conference, pp. 3-12,
(2008).
Steven Seitz, “A Trillion Photos”, EI’13 Keynote (2013).
Electronic Imaging 2013: Color Imaging XVIII
4. Motivation
0 1 2 3 4 5 6
Log Number of Images
Electronic Imaging 2013: Color Imaging XVIII
5. Source Data
ImageClef 2010 snapshot
Adrian Popescu, Theodora Tsikrika and Jana Kludas, "Overview
of the wikipedia retrieval task at ImageCLEF 2010", In the
Working Notes for the CLEF 2010 Workshop, 20-23 September,
Padova, Italy, 2010.
250,000 images plus associated wikipedia data
20 gigabytes
65,000,000,000 pixels uncompressed
Electronic Imaging 2013: Color Imaging XVIII
6. Source Data: At 200 PPI
Electronic Imaging 2013: Color Imaging XVIII
7. Processing
Basic single dual-core (but Open MP threaded) script
to process over all image files
Simple stuff like getting image dimensions can be
done over lunch
Uncompressing all the JPEG files to memory can
take hours
Goal was a color naming algorithm that could be run
in less than a day
Electronic Imaging 2013: Color Imaging XVIII
8. Processing
Some testing done using HP Cloud Services and
compute clusters
But majority of focus on single computing device
Antony Rowstron, Dushyanth Narayanan, Austin Donnelly, Greg
O'Shea, and Andrew Douglas. "Nobody ever got fired for using
hadoop on a cluster", In HotCDP 2012 - 1st International
Workshop on Hot Topics in Cloud Data Processing, (2012).
Electronic Imaging 2013: Color Imaging XVIII
9. Processing
Won’t describe the specifics of the color naming
algorithm (throw produce if you have it) but generally
Input single RGB pixel and output is a single color term
Size of vocabulary or number of color terms is a parameter
Relative range of chroma values corresponding to an achromatic
values is also a parameter
Also currently testing a completely revised model
Finally, in the Future directions section note that the
best option for formal publication is to make use of
currently available open source machine learning
toolboxes.
Electronic Imaging 2013: Color Imaging XVIII
10. Results: Aspect Ratios
Wide range of
image types
Most basic test
of processing
scripts
Electronic Imaging 2013: Color Imaging XVIII
11. Results: Median
Additional test and
visualization of
basic color
properties of images
Large enough data
set was worthwhile
to write custom
HTML5 2d canvas
renderer
Electronic Imaging 2013: Color Imaging XVIII
12. Results: Median
So much data, that
as noted by
Shneiderman the
density plot "uses a
spatial substrate
organizing
principle, but shows
concentrations of
markers” is maybe a
better idea
Data, alpha=0.05
Electronic Imaging 2013: Color Imaging XVIII
13. Results: Max
Max of R+G+B for
the images
Final test of basic
scripting code
Electronic Imaging 2013: Color Imaging XVIII
14. Results
Color terms
across all images
Majority pixels
achromatic
Top chromatic
colors are
arguably natural
tones
Higher chroma
terms relatively
infrequent
Electronic Imaging 2013: Color Imaging XVIII
15. Results
Color Terms for 200,000+ images
60000
Color terms per
image 50000
Peak at 5 are all 40000
achromatic terms
Number of Images
30000
or images
Gradual then 20000
rapid usage of 10000
chromatic terms
0
0 5 10 15 20 25 30 35
Number of Color Terms. Maximum Vocabulary of 30
Electronic Imaging 2013: Color Imaging XVIII
16. Results
Color Terms for 200,000+ images
60000
Sudden drop off
at 30 is a model 50000
failure 40000
Term added to
Number of Images
30000
vocabulary based
on previous 20000
limited
10000
optimization
0
0 5 10 15 20 25 30 35
Number of Color Terms. Maximum Vocabulary of 30
Electronic Imaging 2013: Color Imaging XVIII
17. Current Work
Repeated entire process adjusting the model
parameters
Processing to fill SQL databases
Query the database to validate all of the steps and
explore specific
Electronic Imaging 2013: Color Imaging XVIII
18. Current Work
SELECT * from
cntable order by
skyblue desc limit 40
Electronic Imaging 2013: Color Imaging XVIII
19. Future Directions
Image collections as “pixel
corpora” for algorithm
design, testing and optimization.
Similar to the role that written and spoken
corpora fill for NLP and corpus linguistics
Useful to formalize for citation and
repeatability
Additional analysis features
Testing with more public domain
machine learning algorithms for
repeatability
Electronic Imaging 2013: Color Imaging XVIII
20. Summary
Algorithm optimization, like machine color
naming, with 200,000 images is different than with
200.
Based on Wikipedia, majority of visual content or
pixels are achromatic
Based on Wikipedia, higher chroma named pixels are
less frequent
Based on Wikipedia, there is a gradual then sudden
transition in color term usage
Electronic Imaging 2013: Color Imaging XVIII