A lightweight CNN model for real-time facial expression recognition, trained on the FER-2013 dataset. Classifies emotions into 7 categories: Angry, Disgust, Fear, Happy, Sad, Surprise, and Neutral. Designed for applications in healthcare, security, and human-computer interaction, the model balances accuracy and efficiency streamlined architecture
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A lightweight CNN model for real-time facial expression recognition, trained on the FER-2013 dataset. Classifies emotions into 7 categories: Angry, Disgust, Fear, Happy, Sad, Surprise, and Neutral. Designed for applications in healthcare, security, and human-computer interaction, the model balances accuracy and efficiency streamlined architecture
I-a-coder/FaceExpressionDetection-model
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A lightweight CNN model for real-time facial expression recognition, trained on the FER-2013 dataset. Classifies emotions into 7 categories: Angry, Disgust, Fear, Happy, Sad, Surprise, and Neutral. Designed for applications in healthcare, security, and human-computer interaction, the model balances accuracy and efficiency streamlined architecture
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