8000 GitHub - tharindu326/Emotion-Detector: This aims to classify the emotion on a person's face into some classes, using deep convolutional neural networks (CNN) with 2D convolution layer which creates a convolution kernel that is convolved with the layer input to produce a tensor of outputs. The training network is implemented on Keras and so far it is trained on six set of emotions, [angry, fearful, happy, neutral, sad and surprised]. The model is trained on the FER-2013 dataset which consists of 35887 grayscale, 48x48 sized face images.
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This aims to classify the emotion on a person's face into some classes, using deep convolutional neural networks (CNN) with 2D convolution layer which creates a convolution kernel that is convolved with the layer input to produce a tensor of outputs. The training network is implemented on Keras and so far it is trained on six set of emotions, [a…

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Emotion-Detector

This aims to classify the emotion on a person's face into some classes, using deep convolutional neural networks (CNN) with 2D convolution layer which creates a convolution kernel that is convolved with the layer input to produce a tensor of outputs. The training network is implemented on Keras and so far it is trained on six set of emotions, [angry, fearful, happy, neutral, sad and surprised]. The model is trained on the FER-2013 dataset which consists of 35887 grayscale, 48x48 sized face images.

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This aims to classify the emotion on a person's face into some classes, using deep convolutional neural networks (CNN) with 2D convolution layer which creates a convolution kernel that is convolved with the layer input to produce a tensor of outputs. The training network is implemented on Keras and so far it is trained on six set of emotions, [a…

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