Feb 10, 2017 · This paper presents incremental network quantization (INQ), a novel method, targeting to efficiently convert any pre-trained full-precision ...

Implementing deep convolutional neural networks (CNNs) with boolean arithmetic is ideal for eliminating the notoriously high computational expense of deep ...

This paper presents incremental network quantization (INQ), a novel method, targeting to efficiently convert any pre-trained full-precision convolutional neural ...

This study proposes a more advanced technique, referred to as Quantized Neural Net- work (QNN), for quantizing the neurons and weights during inference and ...

A list of papers, docs, codes about model quantization. This repo is aimed to provide the info for model quantization research, we are continuously ...

Feb 10, 2017 · This paper presents incremental network quantization (INQ), a novel method, targeting to efficiently convert any pre-trained full-precision ...

Aug 25, 2017 · This paper presents incremental network quantization (INQ), a novel method, tar- geting to efficiently convert any pre-trained ...