A feature learning approach for face recognition with robustness to noisy label based on top- prediction
Neurocomputing, pp. 48-55, 2019.
Collecting a vast amount of face data with identity labels to train a convolutional neural network is an effective mean to learn a discriminative feature representation for face recognition. However, the datasets with larger scale often contain more noisy labels, that directly affects the ultimate performance of the learned model. This pa...More
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