Live demonstration: Feature extraction system using restricted Boltzmann machines on FPGA
Kodai Ueyoshi, Takao Marukame, Tetsuya Asai, Masato Motomura, Alexandre Schmid · 2017
Real-time results obtained from an unsupervised feature extraction system using Restricted Boltzmann Machines (RBMs) implemented on FPGA are presented. The feature extraction application is demonstrated using the MNIST dataset, and the weights storing features are visualized in real-time. A digit classification is also performed based on the learning results. Our demonstration system performs 134 times faster than the compared conventional CPU.