Assessing Accuracy of Ensemble Learning for Facial Expression Recognition with CNNs

Automatic facial expression recognition has recently attracted the interest of researchers in the field of computer vision and deep learning. Convolutional Neural Networks (CNNs) have proved to be an effective solution for feature extraction and classification of emotions from facial images. Further, ensembles of CNNs are typically adopted to boost classification performance.

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