SYSTEM AND METHOD FOR DYNAMIC QUANTIZATION FOR DEEP NEURAL NETWORK FEATURE MAPS

A method includes processing, using at least one processor of an electronic device, input data using a first layer of a neural network to generate a feature map. The method also includes representing, using the at least one processor, feature data of the feature map using index values. The index values correspond to multiple records of a look up table (LUT), and the records of the LUT represent a non-uniform distribution of quantization levels of the feature map. The method further includes storing, using the at least one processor, the index values in a memory of the electronic device. The method also includes regenerating, using the at least one processor, the feature data of the feature map by cross-referencing the index values with the LUT. In addition, the method includes processing, using the at least one processor, the feature data using a second layer of the neural network.