1.8k citations · 2.4k across the 36 of their papers we have counts for
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Training Bit Fully Convolutional Network for Fast Semantic Segmentation
He Wen, Shuchang Zhou, Zhe Liang +4
Fully convolutional neural networks give accurate, per-pixel prediction for input images and have applications like semantic segmentation. However, a typical FCN usually requires l…
Effective Quantization Methods for Recurrent Neural Networks
Qinyao He, He Wen, Shuchang Zhou +4
Reducing bit-widths of weights, activations, and gradients of a Neural Network can shrink its storage size and memory usage, and also allow for faster training and inference by exp…
Scene Text Detection via Holistic, Multi-Channel Prediction
Cong Yao, Xiang Bai, Nong Sang +3
Recently, scene text detection has become an active research topic in computer vision and document analysis, because of its great importance and significant challenge. However, vas…
DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients
Shuchang Zhou, Yuxin Wu, Zekun Ni +3
We propose DoReFa-Net, a method to train convolutional neural networks that have low bitwidth weights and activations using low bitwidth parameter gradients. In particular, during…