FPGA-Based Convolutional Autoencoder Implementation

Field-programmable gate array (FPGA) is widely regarded as a promising platform for accelerating Convolutional Autocoders (CAEs). This paper discusses the implementation of a convolutional autoencoder on an FPGA for use in embedded systems. A number of optimizations are proposed to get rid of some problems in the development of such neural networks on FPGA.