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Interactive Real-Time Semantic Querying of Driving Scenes

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Emotion recognition, deep learning, CNN-RNN

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Facial Expression Recognition with Hybrid Models

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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. +

+ 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. +

+ The project focuses on evaluating performance, robustness, and how transfer learning influences emotion recognition across different data conditions. +

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