Compression and Optimization of Neural Networks by Ternarization Methods

Abstract

Current deep neural networks are achieving higher and higher performances, but this comes to a great computational cost which creates a difficulty to use them on embedded platforms like smartphones, tablets, autonomous cars. Fortunately, this can be addressed using quantization techniques, one of which is the internalization when only 3 bits are used.