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23 changes: 23 additions & 0 deletions index.html
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Expand Up @@ -225,6 +225,29 @@ <h3>Interactive Real-Time Semantic Querying of Driving Scenes</h3>
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<div class="teaser" role="img" aria-label="Facial expression recognition with emotion labels and bounding boxes over a human face.">
<img src="assets/group M.png" alt="Facial Expression Recognition Preview" style="position:absolute; inset:0; width:100%; height:100%; object-fit:cover; z-index:2;">
<span class="teaser-label" style="z-index:3;">Group M</span>
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<p class="project-meta">Emotion recognition, deep learning, CNN-RNN</p>
<h3>Facial Expression Recognition with Hybrid Models</h3>
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Can a model reliably read human emotions from a single image? This project explores facial expression recognition by classifying faces into categories such as happiness, sadness, anger, and surprise. We build a small interactive demo that visualizes predicted emotions on input images.
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To achieve this, we combine CNNs for spatial feature extraction with RNNs to capture temporal patterns, comparing pretrained models (MobileNetV2, InceptionV3) with a custom CNN-RNN trained from scratch on FER2013 and CK+ datasets.
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The project focuses on evaluating performance, robustness, and how transfer learning influences emotion recognition across different data conditions.
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