Convolutional neural network channel self-selection compression and acceleration method based on knowledge migration
A convolutional neural network and neural network technology, applied in the field of convolutional neural network channel self-selection compression and acceleration, can solve the problem of capacity reduction and achieve high compression ratio and acceleration ratio
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[0028] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments, but the embodiments of the present invention are not limited thereto.
[0029] Such as figure 1 As shown, the knowledge transfer-based convolutional neural network channel self-selection compression and acceleration method provided in this embodiment includes the following steps:
[0030] S1. Extract migration guidance knowledge from the trained complex convolutional neural network CN1 with sufficient performance.
[0031] The migration guidance knowledge can be extracted from different positions of the network. In this embodiment, the ResNet56 network is used as the complex convolutional neural network CN1, such as figure 2 As shown, the residual module in the figure includes two layers of 3*3 kernel-sized convolutional layers, and in the first residual module of each stage, the step size of the first convolutional layer is 2, using For dimens...
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