zy20030535/Multiple-Pooling-in-Convolutional-Neural-Networks-Max-Range-Pooling-

Model Architecture consist of a convolution layer followed by a Max Pooling layer. The convolution layer is used to create minimum pooling layer, which in turn is subtracted from a max pool layer to obtain a range pooling layer. The max pooling layer and range pooling layers are concatenated to get the final pooling layer.

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