So, the proposed technique aims to replace only max pooling layers by a strided convolution layers using the same filter size and stride of the old pooling layers in order to reduce the model size and improve the accuracy of a CNN. Also, pooling layer is parameter less. However, ...
Pooling more than 64 channels requires the use of a “fused” convolution in the same layer, unless the pooled dimensions are 1×1. Pooling strides can be 1 through 16. For 2D pooling, the stride is the same for both dimensions. For 2D pooling, supported pooling kernel sizes are 1×1...
Quantization and Synthesis (Device Specific Code Generation) for ADI's MAX78000 and MAX78002 Edge AI Devices - dattran-itrvn/ai8x-synthesis
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Pooling does not support padding. Pooling more than 64 channels requires the use of a “fused” convolution in the same layer, unless the pooled dimensions are 1×1. Pooling strides can be 1 through 16. For 2D pooling, the stride is the same for both dimensions. For 2D pooling, supporte...
Pooling does not support padding. Pooling more than 64 channels requires the use of a “fused” convolution in the same layer, unless the pooled dimensions are 1×1. Pooling strides can be 1 through 16. For 2D pooling, the stride is the same for both dimensions. For 2D pooling, supporte...