NORMALIZATION IN DEEP CONVOLUTIONAL NEURAL NETWORKS

    公开(公告)号:US20230237309A1

    公开(公告)日:2023-07-27

    申请号:US18180841

    申请日:2023-03-08

    IPC分类号: G06N3/04 G06N3/08

    CPC分类号: G06N3/04 G06N3/08

    摘要: A device for machine learning is provided, including a first neural network layer, a second neural network layer with a normalization layer arranged in between. The normalization layer is configured to, when the device is undergoing training on a batch of training samples, receive multiple outputs of the first neural network layer for a plurality of training samples of the batch, each output comprising multiple data values for different indices on a first dimension and a second dimension; group the outputs into multiple groups based on the indices on the first and second dimensions; form a normalization output for each group which are provided as input to the second neural network layer. According to the application, the training of a deep convolutional neural network with good performance that performs stably at different batch sizes and is generalizable to multiple vision tasks is achieved, thereby improving the performance of the training.