Emotion Recognition Final Year Projects with Source Code

Byadmin Final Year Projects

Emotion Recognition Final Year Projects for BE, BTech, ME, MSc, MCA and MTech final year engineering students. These Emotion Recognition projects give practical experience and help complete final-year submissions. All projects follow IEEE standards and each project includes source code, project thesis report, presentation, project execution and explanation.

Emotion Recognition Final Year Projects

  1. Identification of Emotions From Facial Gestures in a Teaching Environment With the Use of Machine Learning Techniques
    This project uses computer vision and machine learning to understand students’ emotions in a classroom. It tracks facial gestures to identify feelings like interest, boredom, or enthusiasm during learning. The system builds a database of real, spontaneous emotions and helps teachers evaluate students’ emotional engagement along with their learning progress. It focuses on supporting teachers in face-to-face education.
  2. A Ranking Model for Evaluation of Conversation Partners Based on Rapport Levels
    This project builds a system to rank conversation partners based on how well people get along. It uses data from both speech and text during interactions. Instead of predicting exact scores, it learns which partner is preferred over another. The model helps match people, like students and teachers, in online one-to-one sessions.
  3. A Systematic Review of Facial Expression Detection Methods
    This project studies how computers can recognize human emotions from facial expressions. It reviews many research studies that use deep learning techniques, especially convolutional neural networks. The work compares different methods and datasets to see which are most accurate. It helps understand which AI models work best for emotion detection.
  4. Henry Gas Solubility Optimization With Deep Learning Based Facial Emotion Recognition for Human Computer Interface
    This project focuses on automatically recognizing human emotions from facial expressions. It uses deep learning to analyze faces and detect different emotions. The system removes noise from images, extracts important features, and trains a model to classify emotions accurately. Tests show it works very well, reaching about 99% accuracy.
  5. Modified Earthworm Optimization With Deep Learning Assisted Emotion Recognition for Human Computer Interface
    This project focuses on teaching computers to recognize human emotions from facial expressions. It uses a deep learning model to extract features from faces and an optimization method to improve accuracy. A special algorithm then identifies and classifies the emotions. Tests show that this approach works very well, reaching nearly 99% accuracy.
  6. On the Effect of Log-Mel Spectrogram Parameter Tuning for Deep Learning-Based Speech Emotion Recognition
    This project focuses on recognizing human emotions from speech using deep learning. Instead of testing many complex models, it improves performance by carefully adjusting how speech is converted into visual representations called log-Mel spectrograms. By tuning these settings, the system can detect emotions more accurately on standard speech datasets. The approach shows significant improvement over using default settings.
  7. Enhanced Artificial Vision for Visually Impaired Using Visual Implants
    This project aims to help visually impaired people see better using retinal implants. It uses a camera on glasses to detect people nearby, their age, gender, emotions, and distance. This information is then converted into simple visual patterns that the implant can show to the user. The system works on a small, low-cost device and can run in real time, making it practical for daily use.
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At Final Year Projects, we provide complete guidance for Emotion Recognition IEEE projects for BE, BTech, ME, MSc, MCA and MTech students. We assist at every step from topic selection to coding, report writing, and result analysis.

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Emotion Recognition Project Synopsis & Presentation

Final Year Projects helps prepare Emotion Recognition project synopsis, including problem statement, objectives, existing system, disadvantages, proposed system, advantages and research motivation. We provide PPT slides, tutorials, and full documentation for presentations.

Emotion Recognition Project Thesis Writing

Final Year Projects provides thesis writing services for Emotion Recognition projects. We help BE, BTech, ME, MSc, MCA and MTech students complete their final year project work efficiently.

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