This document describes a proposed system to estimate a person's confidence level based on analyzing their facial expressions and voice during interactions. The system uses convolutional neural networks to classify emotions from facial images. It also analyzes voice samples to detect emotion based on pitch and tone. Both the facial and voice models output confidence levels. The system aims to overcome limitations of existing expression recognition systems and provide a more holistic confidence level reading during questions/answers to help evaluate students or examinees.
STUDENT TEACHER INTERACTION ANALYSIS WITH EMOTION RECOGNITION FROM VIDEO AND ...IRJET Journal
1) The document discusses a study analyzing student-teacher interactions through emotion recognition from video and audio inputs.
2) It aims to understand how students' emotional states relate to comprehension by defining facial behaviors associated with emotions.
3) The study examines the usefulness of recognizing facial expressions and voice between a teacher and student in a classroom setting. It analyzes whether students' facial expressions convey emotions in relation to understanding.
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This document presents a proposed system to analyze the state of mind of an interviewee during an interview using facial expression recognition and classification. The system would use Fisher Face algorithm to detect facial features from video frames and Naive Bayes classification to categorize the detected expressions as indicators of emotional states like happy, sad, angry etc. This automated analysis of facial expressions could provide feedback to improve the interview process and selection of candidates. The summarized system aims to identify an individual's state of mind during an interview through facial expression recognition using deep learning techniques.
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This document discusses facial emotion recognition (FER) and optical character recognition (OCR). It describes the processes involved in FER, including face detection, feature extraction, and expression classification. It also outlines the steps in OCR, such as image acquisition, pre-processing, character segmentation, feature extraction, classification, and post-processing. The document examines related work in FER and OCR and discusses implementations and applications. It explores using FER to analyze user experiences and profiles and the potential risks of inaccurate profiling.
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This document discusses predicting human facial expressions using deep learning. It begins with an introduction to emotion recognition, facial emotion recognition, and deep learning techniques. It then reviews related literature on facial expression recognition using methods like CNNs, active appearance models, and analyzing facial features. The proposed system and methodology are described, including face registration, feature extraction focusing on action units, and using classifiers like KNN, MLP, and SVM to classify emotions based on these features. The goal is to recognize seven basic emotions (neutral, joy, sadness, surprise, anger, fear, disgust) in still images using deep learning techniques.
Facial emoji recognition is a human computer interaction system. In recent times, automatic face recognition or facial expression recognition has attracted increasing attention from researchers in psychology, computer science, linguistics, neuroscience, and similar fields. Facial emoji recognizer is an end user application which detects the expression of the person in the video being captured by the camera. The smiley relevant to the expression of the person in the video is shown on the screen which changes with the change in the expressions. Facial expressions are important in human communication and interactions. Also, they are used as an important tool in studies about behavior and in medical fields. Facial emoji recognizer provides a fast and practical approach for non meddlesome emotion detection. The purpose was to develop an intelligent system for facial based expression classification using CNN algorithm. Haar classifier is used for face detection and CNN algorithm is utilized for the expression detection and giving the emoticon relevant to the expression as the output. N. Swapna Goud | K. Revanth Reddy | G. Alekhya | G. S. Sucheta ""Facial Emoji Recognition"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23166.pdf
Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/23166/facial-emoji-recognition/n-swapna-goud
IRJET-Human Face Detection and Identification using Deep Metric LearningIRJET Journal
This document discusses a project that uses deep metric learning techniques for human face detection and identification in images and videos. Deep metric learning outputs a real-valued vector rather than a single classification. It uses libraries like OpenCV, Dlib, scikit-learn and Keras to build neural networks for facial recognition. The goals are to develop a system that can identify faces even from low quality images with variations in illumination, expression, angle and occlusions. Existing face recognition has challenges in these conditions, so the aim is to improve accuracy rates for normal and non-ideal images through deep metric learning approaches.
This document presents a facial expression recognition system that identifies and classifies seven basic expressions: happy, surprise, fear, disgust, sad, anger, and a neutral state. The system consists of four main parts: image acquisition, pre-processing, feature extraction, and classification. It was developed using both OpenCV and a web-based JavaScript approach. The system was tested on both real-time and pre-recorded video streams and can identify emotions in images and video input from a webcam in real-time. Evaluation showed the JavaScript implementation using a generalized dataset provided more accurate real-time predictions compared to the OpenCV approach.
IRJET- Women Security Alert using Face RecognitionIRJET Journal
This document describes a facial recognition system to improve women's security. It uses face detection and the Local Binary Pattern technique to extract facial features from images. The system then classifies facial expressions to recognize emotions like happy, sad, fear, etc. It aims to identify a person's emotion and send alerts according to the emotion detected. The system could help ensure women's safety by monitoring emotions and sending timely alerts or notifications.
STUDENT TEACHER INTERACTION ANALYSIS WITH EMOTION RECOGNITION FROM VIDEO AND ...IRJET Journal
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IRJET- An Innovative Approach for Interviewer to Judge State of Mind of an In...IRJET Journal
This document presents a proposed system to analyze the state of mind of an interviewee during an interview using facial expression recognition and classification. The system would use Fisher Face algorithm to detect facial features from video frames and Naive Bayes classification to categorize the detected expressions as indicators of emotional states like happy, sad, angry etc. This automated analysis of facial expressions could provide feedback to improve the interview process and selection of candidates. The summarized system aims to identify an individual's state of mind during an interview through facial expression recognition using deep learning techniques.
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This document discusses facial emotion recognition (FER) and optical character recognition (OCR). It describes the processes involved in FER, including face detection, feature extraction, and expression classification. It also outlines the steps in OCR, such as image acquisition, pre-processing, character segmentation, feature extraction, classification, and post-processing. The document examines related work in FER and OCR and discusses implementations and applications. It explores using FER to analyze user experiences and profiles and the potential risks of inaccurate profiling.
IRJET- Prediction of Human Facial Expression using Deep LearningIRJET Journal
This document discusses predicting human facial expressions using deep learning. It begins with an introduction to emotion recognition, facial emotion recognition, and deep learning techniques. It then reviews related literature on facial expression recognition using methods like CNNs, active appearance models, and analyzing facial features. The proposed system and methodology are described, including face registration, feature extraction focusing on action units, and using classifiers like KNN, MLP, and SVM to classify emotions based on these features. The goal is to recognize seven basic emotions (neutral, joy, sadness, surprise, anger, fear, disgust) in still images using deep learning techniques.
Facial emoji recognition is a human computer interaction system. In recent times, automatic face recognition or facial expression recognition has attracted increasing attention from researchers in psychology, computer science, linguistics, neuroscience, and similar fields. Facial emoji recognizer is an end user application which detects the expression of the person in the video being captured by the camera. The smiley relevant to the expression of the person in the video is shown on the screen which changes with the change in the expressions. Facial expressions are important in human communication and interactions. Also, they are used as an important tool in studies about behavior and in medical fields. Facial emoji recognizer provides a fast and practical approach for non meddlesome emotion detection. The purpose was to develop an intelligent system for facial based expression classification using CNN algorithm. Haar classifier is used for face detection and CNN algorithm is utilized for the expression detection and giving the emoticon relevant to the expression as the output. N. Swapna Goud | K. Revanth Reddy | G. Alekhya | G. S. Sucheta ""Facial Emoji Recognition"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23166.pdf
Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/23166/facial-emoji-recognition/n-swapna-goud
IRJET-Human Face Detection and Identification using Deep Metric LearningIRJET Journal
This document discusses a project that uses deep metric learning techniques for human face detection and identification in images and videos. Deep metric learning outputs a real-valued vector rather than a single classification. It uses libraries like OpenCV, Dlib, scikit-learn and Keras to build neural networks for facial recognition. The goals are to develop a system that can identify faces even from low quality images with variations in illumination, expression, angle and occlusions. Existing face recognition has challenges in these conditions, so the aim is to improve accuracy rates for normal and non-ideal images through deep metric learning approaches.
This document presents a facial expression recognition system that identifies and classifies seven basic expressions: happy, surprise, fear, disgust, sad, anger, and a neutral state. The system consists of four main parts: image acquisition, pre-processing, feature extraction, and classification. It was developed using both OpenCV and a web-based JavaScript approach. The system was tested on both real-time and pre-recorded video streams and can identify emotions in images and video input from a webcam in real-time. Evaluation showed the JavaScript implementation using a generalized dataset provided more accurate real-time predictions compared to the OpenCV approach.
IRJET- Women Security Alert using Face RecognitionIRJET Journal
This document describes a facial recognition system to improve women's security. It uses face detection and the Local Binary Pattern technique to extract facial features from images. The system then classifies facial expressions to recognize emotions like happy, sad, fear, etc. It aims to identify a person's emotion and send alerts according to the emotion detected. The system could help ensure women's safety by monitoring emotions and sending timely alerts or notifications.
MUSIC RECOMMENDATION THROUGH FACE RECOGNITION AND EMOTION DETECTIONIRJET Journal
This document describes a system for music recommendation based on facial emotion recognition using convolutional neural networks. It analyzes facial images using CNN models to detect seven basic emotions. Based on the detected emotion, it recommends songs from predefined playlists that match the user's mood. The system architecture inputs images of the user's face, uses a CNN for emotion detection, and then selects appropriate music from playlists organized by emotion. It was developed to provide personalized music recommendations based on a user's real-time facial expressions and emotional state, unlike other systems that rely only on search queries or prior listening history.
Automatic Emotion Recognition Using Facial Expression: A ReviewIRJET Journal
This document reviews automatic emotion recognition using facial expressions. It discusses how facial expressions are an important form of non-verbal communication that can express human perspectives and mental states. The document then summarizes several popular techniques for automatic facial expression recognition systems, including those based on statistical movement, auto-illumination correction, identification-driven emotion recognition for social robots, e-learning approaches, cognitive analysis for interactive TV, and motion detection using optical flow. Each technique is assessed in terms of its pros and cons. The goal of the techniques is to enhance human-computer interaction through more accurate and real-time recognition of facial expressions and emotions.
IRJET- Facial Expression Recognition using Deep Learning: A ReviewIRJET Journal
This document provides a review of facial expression recognition using deep learning approaches. It begins with an introduction to facial expression recognition and its applications. It then discusses commonly used datasets for facial expression recognition, including image-based datasets like JAFFE and video-based datasets like CK+. The document reviews 26 previous research papers that used deep learning methods like convolutional neural networks for facial expression recognition. It concludes that convolutional neural networks provide more accurate results for facial expression recognition compared to traditional methods.
AI Therapist – Emotion Detection using Facial Detection and Recognition and S...ijtsrd
This paper presents an integrated system for emotion detection using facial detection and recognition. we have taken into account the fact that emotions are most widely represented with eyes and mouth expressions. In this research effort, we implement a general convolutional neural network CNN building framework for designing real time CNNs. We validate our models by creating a real time vision system that accomplishes the tasks of face detection, emotion classification, and generating the content according to the emotion or mood of the person simultaneously in one blended step using our proposed CNN architecture. Our proposed model consisted of modules such as image processing, Feature extraction, feature classification, and recommendation process. The images used in the experiment are pre processed with various image processing methods like canny edge detection, histogram equalization, fit ellipse, and FER dataset is mediated for conducting the experiments. With a trained profile that can be updated flexibly, a user can detect his her behavior on a real time basis. It utilizes the state of the art of face detection and recognition algorithms. Sanket Godbole | Jaivardhan Shelke "AI Therapist – Emotion Detection using Facial Detection and Recognition & Showing Content According to Emotions" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33267.pdf Paper Url: https://www.ijtsrd.com/computer-science/artificial-intelligence/33267/ai-therapist-–-emotion-detection-using-facial-detection-and-recognition-and-showing-content-according-to-emotions/sanket-godbole
Synopsis of Facial Emotion Recognition to Emoji ConversionIRJET Journal
This document describes a project to develop a real-time facial emotion recognition system using OpenCV, TensorFlow, and NumPy. The system aims to identify human emotions from facial expressions captured by a webcam and convert the recognized emotions into corresponding emojis. A model will be trained on a large dataset of labeled facial images to classify emotions. OpenCV will handle image and video processing, TensorFlow will enable machine learning, and NumPy will optimize computation. The goals are to accurately recognize a wide range of emotions in real-time, provide a user-friendly interface, and enhance the user experience through emotion-to-emoji conversion. Thorough testing will evaluate the system's performance.
This document discusses speech emotion recognition using various machine learning classifiers. It begins with an abstract describing speech emotion recognition and its applications. It then discusses the methodology, which includes preprocessing audio files from the RAVDESS dataset, extracting features like MFCCs and chroma, and classifying emotions using classifiers like Catboost, XGB, HistGradient Boosting, and MLP. The methodology achieves 83.33% accuracy in classifying emotions like happy, calm, disgust, and fearful using these classifiers, outperforming a prior method with 81% accuracy.
Age and Gender Classification using Convolutional Neural NetworkIRJET Journal
This document describes a study that aims to accurately identify the gender and age range of facial images using convolutional neural networks. It begins with an introduction to age and gender classification and some of the challenges. It then discusses the system analysis and design, including the use of convolutional neural networks and machine learning techniques. The implementation section notes that Python, TensorFlow, Keras and OpenCV will be used to build a convolutional neural network model to detect faces in images and predict age and gender through training on available datasets. The overall goal is to develop an accurate system for age and gender detection from facial images.
IRJET- Techniques for Analyzing Job Satisfaction in Working Employees – A...IRJET Journal
The document discusses techniques for analyzing job satisfaction in employees using deep learning algorithms. It proposes applying convolutional neural networks (CNNs) to facial images taken at regular intervals to classify emotions and determine if an employee is happy or stressed. CNNs would be trained to recognize emotions like surprise, fear, disgust, anger, happiness and sadness from facial expressions. The percentage of positive versus negative emotions detected over multiple images could indicate an employee's level of satisfaction. A literature review discusses limitations of existing approaches and supports using CNNs on facial expressions for more accurate analysis of employee mental health and work satisfaction.
ANALYSING SPEECH EMOTION USING NEURAL NETWORK ALGORITHMIRJET Journal
The document proposes a deep learning model to identify speech emotion using neural network algorithms. It discusses using convolutional neural networks and LSTM to extract acoustic features from speech signals and accurately identify emotional states. The model aims to improve the accuracy and robustness of speech emotion recognition systems, with applications in healthcare, customer service, and human-computer interaction.
IRJET- Sentimental Analysis on Audio and Video using Vader Algorithm -Monali ...IRJET Journal
This document presents a proposed system for performing sentiment analysis on audio and video reviews from social media platforms. The system first collects audio and video data from sites like YouTube and Facebook. It then separates the audio and video files, converts them to .wav format, and extracts text from the audio and video files. This extracted text is then analyzed using the VADER sentiment analysis algorithm to determine the sentiment polarity (positive, negative, neutral) expressed in the text. VADER is a lexicon-based approach that rates words based on sentiment and calculates overall sentiment scores. The proposed system aims to analyze sentiment in audio and video reviews to better understand user opinions expressed across various social media platforms.
This document summarizes face recognition technology. It discusses how face recognition works by measuring facial landmarks and creating a face print for identification and verification purposes. Recent advances include 3D facial recognition, which can identify faces from different angles. The document outlines the history of facial recognition and discusses current and potential uses, such as border security and airport passenger screening. It also notes some limitations, such as the potential for privacy issues and identity theft if the data is compromised.
This document summarizes face recognition technology. It discusses how face recognition works by measuring facial landmarks and creating a face print for identification and verification purposes. Recent advances include 3D facial recognition, which can identify faces from different angles. The document outlines the history of facial recognition and discusses current and potential uses, such as border security and ATM verification. However, it also notes privacy and security concerns about the use of facial recognition without consent.
Emotion Recognition through Speech Analysis using various Deep Learning Algor...IRJET Journal
This document summarizes a research paper on emotion recognition through speech analysis using deep learning algorithms. The researchers used datasets containing speech samples labeled with seven emotions to train and test convolutional neural network (CNN), support vector machine (SVM), recurrent neural network (RNN), and random forest models. They found that the RNN model achieved the highest testing accuracy at 75.31% for emotion recognition. The researchers concluded that speech emotion recognition systems could be useful for applications like dialogue systems, call centers, student voice reviews, and building healthy relationships.
Development of video-based emotion recognition using deep learning with Googl...TELKOMNIKA JOURNAL
Emotion recognition using images, videos, or speech as input is considered as a hot topic in the field of research over some years. With the introduction of deep learning techniques, e.g., convolutional neural networks (CNN), applied in emotion recognition, has produced promising results. Human facial expressions are considered as critical components in understanding one's emotions. This paper sheds light on recognizing the emotions using deep learning techniques from the videos. The methodology of the recognition process, along with its description, is provided in this paper. Some of the video-based datasets used in many scholarly works are also examined. Results obtained from different emotion recognition models are presented along with their performance parameters. An experiment was carried out on the fer2013 dataset in Google Colab for depression detection, which came out to be 97% accurate on the training set and 57.4% accurate on the testing set.
Real Time Facial Expression Recognition and Imitationijtsrd
This document summarizes a research paper on real-time facial expression recognition and imitation using a Raspberry Pi. The paper proposes a system that uses a Raspberry Pi equipped with a camera to detect faces in real-time, recognize facial expressions (neutral, happy, sad, surprise), and display the recognized expression. It uses Viola-Jones detection and Active Shape Modeling for feature extraction to classify expressions based on a trained CNN model. The system is intended to support applications in human-computer interaction and medical monitoring by automatically recognizing a person's emotions from facial images in real-time.
Covid Mask Detection and Social Distancing Using Raspberry piIRJET Journal
This document describes a system that uses computer vision and machine learning to detect if individuals are wearing masks and maintaining proper social distancing in public places. The system uses a Raspberry Pi connected to a USB camera to take photos and video. Convolutional neural network models like CNN and YOLO are used to analyze the images, detect faces, and determine if masks are being worn correctly. If individuals are not wearing masks or social distancing, the system will provide an alert or sound from a connected speaker. The goal is to help enforce mask and distancing guidelines without needing human monitoring, in order to reduce virus spread during the COVID-19 pandemic.
IRJET- Characteristics and Mood Prediction of Human by Signature and Facial E...IRJET Journal
This document discusses techniques for predicting human mood and behavior through analysis of signatures and facial expressions. It proposes using the Improved Susan method to recognize facial expressions based on mouth features extracted using edge detection. Eigenvector approach with principal component analysis is also used for facial expression recognition. Signature analysis examines features like pen pressure and alignment extracted from signatures to predict behavior using support vector machines and radial basis functions. The methods are tested on standard datasets and experimental results demonstrate their ability to accurately recognize different expressions and predict behavior.
IRJET- Sentimental Analysis on Audio and VideoIRJET Journal
1) The document discusses sentiment analysis on audio and video content using techniques like automatic speech recognition and behavior detection. It aims to analyze sentiment expressed by entities in natural audio and video.
2) Sentiment detection has been explored more for text, while video sentiment detection is relatively under-explored. The proposed approach uses algorithms to tag audio with text, and can extend to detect scenarios and behaviors in video after audio and video feature extraction.
3) The approach uses part-of-speech tagging to extract text features for sentiment classification (positive or negative) using support vector machines and evaluates on public text and video datasets. This allows identification of keywords/phrases carrying important information to enhance search.
IRJET- Persons Identification Tool for Visually Impaired - Digital EyeIRJET Journal
This document presents a face detection and recognition system to help visually impaired people identify individuals. The system uses computer vision techniques like convolutional neural networks and cascade classifiers for face detection with high accuracy. It then performs face recognition on pre-trained image datasets to determine a person's identity, as well as their emotion, age and gender. The system was tested on a combined dataset of images and achieved 95.7% accuracy in identifying faces, even when there were many faces present. This person identification tool aims to help the visually impaired better interact with others by audibly providing the name and attributes of detected individuals.
INDIAN SIGN LANGUAGE TRANSLATION FOR HARD-OF-HEARING AND HARD-OF-SPEAKING COM...IRJET Journal
This document proposes a system to translate Indian sign language to text and speech in real-time using machine learning. It aims to help communication between the hard-of-hearing and hard-of-speaking communities by eliminating the need for interpreters. The system would use a webcam or phone camera to capture sign language gestures which are then preprocessed and fed into a convolutional neural network model to recognize the signs and output the translation as text. Previous studies that used other methods like CNNs, RNNs, and HMMs to translate sign language are summarized along with their accuracies ranging from 91.5% to 99%. The proposed system architecture involves capturing gestures, preprocessing, detecting the sign, and displaying the translation for sign to text
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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Emotion recognition using images, videos, or speech as input is considered as a hot topic in the field of research over some years. With the introduction of deep learning techniques, e.g., convolutional neural networks (CNN), applied in emotion recognition, has produced promising results. Human facial expressions are considered as critical components in understanding one's emotions. This paper sheds light on recognizing the emotions using deep learning techniques from the videos. The methodology of the recognition process, along with its description, is provided in this paper. Some of the video-based datasets used in many scholarly works are also examined. Results obtained from different emotion recognition models are presented along with their performance parameters. An experiment was carried out on the fer2013 dataset in Google Colab for depression detection, which came out to be 97% accurate on the training set and 57.4% accurate on the testing set.
Real Time Facial Expression Recognition and Imitationijtsrd
This document summarizes a research paper on real-time facial expression recognition and imitation using a Raspberry Pi. The paper proposes a system that uses a Raspberry Pi equipped with a camera to detect faces in real-time, recognize facial expressions (neutral, happy, sad, surprise), and display the recognized expression. It uses Viola-Jones detection and Active Shape Modeling for feature extraction to classify expressions based on a trained CNN model. The system is intended to support applications in human-computer interaction and medical monitoring by automatically recognizing a person's emotions from facial images in real-time.
Covid Mask Detection and Social Distancing Using Raspberry piIRJET Journal
This document describes a system that uses computer vision and machine learning to detect if individuals are wearing masks and maintaining proper social distancing in public places. The system uses a Raspberry Pi connected to a USB camera to take photos and video. Convolutional neural network models like CNN and YOLO are used to analyze the images, detect faces, and determine if masks are being worn correctly. If individuals are not wearing masks or social distancing, the system will provide an alert or sound from a connected speaker. The goal is to help enforce mask and distancing guidelines without needing human monitoring, in order to reduce virus spread during the COVID-19 pandemic.
IRJET- Characteristics and Mood Prediction of Human by Signature and Facial E...IRJET Journal
This document discusses techniques for predicting human mood and behavior through analysis of signatures and facial expressions. It proposes using the Improved Susan method to recognize facial expressions based on mouth features extracted using edge detection. Eigenvector approach with principal component analysis is also used for facial expression recognition. Signature analysis examines features like pen pressure and alignment extracted from signatures to predict behavior using support vector machines and radial basis functions. The methods are tested on standard datasets and experimental results demonstrate their ability to accurately recognize different expressions and predict behavior.
IRJET- Sentimental Analysis on Audio and VideoIRJET Journal
1) The document discusses sentiment analysis on audio and video content using techniques like automatic speech recognition and behavior detection. It aims to analyze sentiment expressed by entities in natural audio and video.
2) Sentiment detection has been explored more for text, while video sentiment detection is relatively under-explored. The proposed approach uses algorithms to tag audio with text, and can extend to detect scenarios and behaviors in video after audio and video feature extraction.
3) The approach uses part-of-speech tagging to extract text features for sentiment classification (positive or negative) using support vector machines and evaluates on public text and video datasets. This allows identification of keywords/phrases carrying important information to enhance search.
IRJET- Persons Identification Tool for Visually Impaired - Digital EyeIRJET Journal
This document presents a face detection and recognition system to help visually impaired people identify individuals. The system uses computer vision techniques like convolutional neural networks and cascade classifiers for face detection with high accuracy. It then performs face recognition on pre-trained image datasets to determine a person's identity, as well as their emotion, age and gender. The system was tested on a combined dataset of images and achieved 95.7% accuracy in identifying faces, even when there were many faces present. This person identification tool aims to help the visually impaired better interact with others by audibly providing the name and attributes of detected individuals.
INDIAN SIGN LANGUAGE TRANSLATION FOR HARD-OF-HEARING AND HARD-OF-SPEAKING COM...IRJET Journal
This document proposes a system to translate Indian sign language to text and speech in real-time using machine learning. It aims to help communication between the hard-of-hearing and hard-of-speaking communities by eliminating the need for interpreters. The system would use a webcam or phone camera to capture sign language gestures which are then preprocessed and fed into a convolutional neural network model to recognize the signs and output the translation as text. Previous studies that used other methods like CNNs, RNNs, and HMMs to translate sign language are summarized along with their accuracies ranging from 91.5% to 99%. The proposed system architecture involves capturing gestures, preprocessing, detecting the sign, and displaying the translation for sign to text
Similar to CONFIDENCE LEVEL ESTIMATOR BASED ON FACIAL AND VOICE EXPRESSION RECOGNITION AND CLASSIFICATION (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.
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.
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.
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...PriyankaKilaniya
Energy efficiency has been important since the latter part of the last century. The main object of this survey is to determine the energy efficiency knowledge among consumers. Two separate districts in Bangladesh are selected to conduct the survey on households and showrooms about the energy and seller also. The survey uses the data to find some regression equations from which it is easy to predict energy efficiency knowledge. The data is analyzed and calculated based on five important criteria. The initial target was to find some factors that help predict a person's energy efficiency knowledge. From the survey, it is found that the energy efficiency awareness among the people of our country is very low. Relationships between household energy use behaviors are estimated using a unique dataset of about 40 households and 20 showrooms in Bangladesh's Chapainawabganj and Bagerhat districts. Knowledge of energy consumption and energy efficiency technology options is found to be associated with household use of energy conservation practices. Household characteristics also influence household energy use behavior. Younger household cohorts are more likely to adopt energy-efficient technologies and energy conservation practices and place primary importance on energy saving for environmental reasons. Education also influences attitudes toward energy conservation in Bangladesh. Low-education households indicate they primarily save electricity for the environment while high-education households indicate they are motivated by environmental concerns.
Supermarket Management System Project Report.pdfKamal Acharya
Supermarket management is a stand-alone J2EE using Eclipse Juno program.
This project contains all the necessary required information about maintaining
the supermarket billing system.
The core idea of this project to minimize the paper work and centralize the
data. Here all the communication is taken in secure manner. That is, in this
application the information will be stored in client itself. For further security the
data base is stored in the back-end oracle and so no intruders can access it.
Software Engineering and Project Management - Introduction, Modeling Concepts...Prakhyath Rai
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
Design and optimization of ion propulsion dronebjmsejournal
Electric propulsion technology is widely used in many kinds of vehicles in recent years, and aircrafts are no exception. Technically, UAVs are electrically propelled but tend to produce a significant amount of noise and vibrations. Ion propulsion technology for drones is a potential solution to this problem. Ion propulsion technology is proven to be feasible in the earth’s atmosphere. The study presented in this article shows the design of EHD thrusters and power supply for ion propulsion drones along with performance optimization of high-voltage power supply for endurance in earth’s atmosphere.
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