An Implementation of ResNet on the Classification of RGB-D Images

Facial recognition is to identify human faces from an image. It is becoming more and more important these days as it can be applied in multiple industries, such as bank, airport, e-business, etc. Because of the broad application prospects, face recognition is actively developed and researched by many people, companies and academic organizations. In this paper, we customize one of the facial recognition models developed in the recent years – ResNet on the Intellifusion 3D face dataset [1]. And then we evaluate the performance of the algorithm by adjusting the depth of the network, pre-processing steps of the pictures and also the learning rate.

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