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32 articles for “Emotion Detection Recognition”
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FACE EMOTION RECOGNITION TO DETECT DEPRESSION
Abstract: In the current competitive world, one of the most familiar and grave mental illness we encounter in humans is Depression also called as major depression or major depressive disorder. It makes you feel depressed and disinterested all the time, which has a bad impact on your thoughts and behaviour. Thus affecting not only the victim but also people associated with them, such as family, friends and society. If not treated …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 1–14 Read article
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Facial Emotion Recognition Using CNN and OpenCV: A Review
Abstract: Emotion Recognition Using a Facial Feature Recognition is a prominent area of study in the world of Human Computer Interaction (HCI). Humans may express a wide range of emotions and moods through facial movements and body language. In this project, in order to detect the live emotions from the human facial gesture, we will be using an algorithm that allows the computer to automatically detect the facial recognition of human …
Published in Journal of Open Source Developments · Vol. 10, Issue 1, 2023 · pp. 1–9 Read article
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Real-time Facial Recognition with Convolutional Neural Networks for Personalized Music Therapy
Abstract: In this project, a web-based application has been developed that integrates computer vision-based facial recognition, multiple algorithms, and machine learning approaches. The given system obtains a user’s emotions in the real-time frame by analyzing facial expressions such as eyes, mouth, the forehead, and so on. It detects emotions like happiness, sadness, that is neutrality, or rock. For a given detected emotion, language, and a user’s chosen artist, the system recommends …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 67–76 Read article
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Emotion Recognition Through Image Processing for Improving Human Computer Interaction
Abstract: Detection and extracting various emotions and then validating those emotions from facial expression have become very important for improving the overall human-computer interaction. Emotion detection has several applications in areas such as artificial intelligence, image processing, intelligent Human-Computer interfaces. This paper reviews the literature on different aspects like different theories of emotions, methods of detecting emotions like face detection, eye detection, lip detection. This paper reviews comparative techniques for recognizing …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 1, 2015 · pp. 31–35 Read article
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Age, Gender And Emotion Detection
Abstract: The main reason is the development of a method to automatically estimate the age and gender of the human face. It continues to play an important role in computer vision and pattern recognition. In addition to age determination, facial emotion recognition also plays an important role in computer vision. Nonverbal communication methods such as facial expressions, eye movements, and gestures are used in many human-computer interaction applications. Much research has …
Published in Recent Trends in Sensor Research & Technology · Vol. 9, Issue 1, 2022 · pp. 1–6 Read article
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Control the Robot via Both Voice & Moblie Application in Departmental Information Robot
Abstract: The concept and development of an autonomous, interactive humanoid robot created to deliver college information via voice and mobile application control are presented in this work. To facilitate easy user interaction with the robot, the suggested system combines intelligent control, wireless connection, and speech recognition. The robot is equipped with a 10-inch monitor that provides instructors and students with information about college departments, facilities, and services. Oral responses from a …
Published in Recent Trends in Electronics Communication Systems · Vol. 13, Issue 2, 2026 Read article
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An Unsupervised Common Sense-based Learning Framework for Emotion Detection and Classification in Textual Social Data
Abstract: AbstractEmotions are inherent to human behavior and generally expressed in response to the stimuli from the external environment or some internal processes. With the widespread use of online social platforms, people often express themselves using tweets, blogs and posts which generally include affective text. The topic of emotion detection and recognition has been widely studied in computational science and in fact a separate area “Affective Computing” is dedicated to its …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 4, Issue 3, 2017 · pp. 44–51 Read article
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A Profound Analysis on Complex Multiclass BCI Signals Classification by an EEG Device
Abstract: With a major shift in the technology paradigm today in the area of deep learning and artificial intelligence, one of its important applications today is found in brain-computer interface (BCI). Brain computer-interface, also known as neural control interface or mind-machine interface is a device that helps a user to interact with a computer using only his brain-activity, which is measured usually by Electroencephalography (EEG). The usage of such mechanism has …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 8, Issue 1, 2021 · pp. 22–44 Read article
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Music Recommendation System and Mood Tweak Using Facial Emotion Recognition
Abstract: A user’s emotions can be detected through their facial expressions, these characteristics can be parsed, and the information can be used to improve the user’s experience. With the computing capabilities of on-board graphic processing, there is a new trend of functionality being considered in the field of emotion detection. The use of Convolutional and Recurring Neural Networks (CNN & RNN) to conduct a comparison on which deep learning can be …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 9, Issue 1, 2022 · pp. 43–49 Read article
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Empowering Vehicle: The Impact of Deep and Reinforcement Learning in IoV
Abstract: Deep learning and reinforcement learning represent two pivotal pillars within the realm of artificial intelligence and machine learning, bearing transformative potential in the domain of the Internet of Vehicles (IoV). This abstract explores the multifaceted applications of these cutting-edge techniques within the IoV framework. Deep learning, exemplified by convolution neural networks (CNNs) and recurrent neural networks (RNNs), empowers IoV systems with the prowess to discern complex patterns in sensory data. …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 2, 2025 · pp. 1–12 Read article
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AI-Powered Emotion Recognition in Dog
Abstract: Understanding animal emotions is important for improving veterinary care, human animal interaction, and overall pet well-being. Inspired by previous research that utilized a modified EfficientNetB5 model for emotion classification in cats and dogs, our study builds upon this foundation with a focus on real-time emotion recognition in dogs. While earlier approaches achieved high accuracy using Dense Residual and Squeeze-and-Excitation blocks, they often lacked real-time applicability and were not optimized for …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 · pp. 20–32 Read article
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Comparison and Analysis of Facial Emotion Detection Using Various Deep Learning Neural Networks
Abstract: Facial emotion recognition employs Convolutional Neural Networks (CNNs), Residual Networks (ResNet), Long Short-Term Memory (LSTM) networks, and Deep Neural Networks (DNNs) to automatically identify various emotions, including disgust, anger, fear, happiness, sadness, surprise, and neutrality. This study utilizes transfer learning along with data preprocessing techniques such as rotation, flipping, brightness adjustment, and enhancement methods. Traditional machine learning models achieve an accuracy range of 45 to 50%. In contrast, our proposed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 37–42 Read article
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Facial Emotion Detection and Its Applications
Abstract: Facial emotion detection (FED) is an interdisciplinary field that integrates artificial intelligence, computer vision, and machine learning to recognize and interpret human emotions based on facial expressions. The development of FED systems has been propelled by advancements in deep learning, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which enhance recognition accuracy. Feature extraction techniques, including geometric and appearance-based methods, play a crucial role in classifying emotional states. …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 8–12 Read article
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Speech Emotion Recognition using Convolutional Neural Networks
Abstract: This research work presents an assortment of techniques in Speech Emotion Recognition with the help of spectrograms and handcrafted Deep learning architecture: Convolutional Neural Networks (CNN). Emotional kingdom detection is a crucial part of human-device interplay studies. To make interaction between man and machine more natural, many milestones are conquered in speech emotion recognition, but still this process requires more up-to-the-mark results. To make an attempt for the same, this …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 3, 2021 · pp. 26–32 Read article
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EMOTION RECOGNITION FROM ELECTROENCEPHALOGRAM SIGNAL AND EYE MOVEMENT BASED ON DEEP LEARNING
Abstract: Emotion recognition from electroencephalogram (EEG) signals has gained significant attention due to its potential in human- computer interaction (HCI), mental health monitoring, and personalized content delivery. This paper presents the use of Convolutional neural networks (CNNs) to classify emotions such as happiness, sadness, fear, neutral, and disgust by leveraging a fusion of EEG signals and eye movements data. Compared to conventional methods of emotion detection, such as those that rely …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 8–15 Read article
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Procedure for Conventional Facial Emotion Detection Algorithms Based on Machine Learning
Abstract: Researchers in psychology, computer science, linguistics, neurology, and allied fields have become more interested in a human-computer interface system for autonomous face recognition or facial expression recognition. This study has recommended an Automatic Facial Expression Recognition System (AFERS). The proposed methodology consists of face detection, feature extraction, and facial expression identification processes. The initial phases of the face detection procedure include skin color identification using the YCbCr color model, illumination …
Published in International Journal of Electronics Automation · Vol. 1, Issue 1, 2023 · pp. 07–13 Read article
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Blue Eye Technology
Abstract: In social interaction with other human beings which delivers information by using emotion and facial expression play about their mood that is important part in communication. The “Blue Eyes Technology” creates sensory abilities like those of human beings which enable the computer to gather facts about humans and interact with others. This paper implements the detection of feelings or emotion like fear, surprised, happy, sad and anger; it defines by …
Published in Journal of Advancements in Robotics · Vol. 7, Issue 1, 2020 · pp. 15–18 Read article
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Facial Expression Recognition Using Convolutional Neural Network
Abstract: The recognition of facial expression is a key step in nonverbal human communication in the field of computer vision. The Facial Expression Recognition (FER) system reflects emotions as well as mental activities, social interaction with people and expressing positive or negative attitude in general. It has many applications like human machine interaction, understanding human behavior and emotions, mental state identification, drowsiness detection for driving safety and health care. One of …
Published in Journal of Open Source Developments · Vol. 6, Issue 1, 2019 · pp. 18–27 Read article
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Mood Mate: A Solid-State Edge-AI System for Real-Time Facial Emotion Recognition
Abstract: Recent progress in solid-state electronics and embedded vision systems has enabled real-time emotion-aware applications at the edge. This paper presents MoodMate, a solid-state edge-AI framework for real-time facial emotion recognition using camera-based sensing and embedded processing. The proposed system integrates a solid-state image sensor with an AI- driven emotion classification pipeline optimized for low-latency and resource-constrained environments. Intelligent, emotion-aware apps can now be deployed right at the network edge thanks …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 24–30 Read article
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Human Robot Interface and Visual Compressive Detecting on Robot Arm
Abstract: Vision compressive sensing, brain machine reference commands, and adaptive controller have been effectively integrated that enable the robot to perform manipulation tasks as guided by human operator’s mind and according to its innovative views. The ideology proposed consists of following main phases: (1) action recognition (2) hardware interfacing. Initially action recognition captures video according to movements enacted in recognition system. Later, in hardware interfacing it passes required commands by a …
Published in Current Trends in Information Technology · Vol. 8, Issue 3, 2018 · pp. 5–12 Read article