Convolutional neural network with sparse and complementary kernels

A computer-implemented method, comprising:

• analyzing, by a system operatively coupled to a processor, an initial convolutional layer in a network architecture of a convolutional neural network and one or more subsequent convolutional layers in the network architecture;
• replacing, by the system, original convolutional kernels in the initial convolutional layer with initial sparse convolutional kernels;
• and
• replacing, by the system, subsequent convolutional kernels in one or more subsequent convolutional layers with complementary sparse convolutional kernels, wherein the complementary sparse convolutional kernels have a complementary pattern with respect to sparse kernels of a previous convolutional layer.

A computer program product facilitating providing efficient convolution neural networks and comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:

• analyze a network architecture and a trained model of a convolutional neural network to determine original convolutional kernels in an initial convolutional layer and determine one or more subsequent convolutional layers in the network architecture;
• replace the original convolutional kernels in the initial convolutional layer with initial sparse convolutional kernels;
• and
• replace subsequent convolutional kernels in one or more subsequent convolutional layers with complementary sparse convolutional kernels, wherein the complementary sparse convolutional kernels have a complementary pattern with respect to sparse kernels of a previous convolutional layer.