88 citations · 102 across the 10 of their papers we have counts for
4 papers · 1 filter
Robust Training of Neural Networks at Arbitrary Precision and Sparsity
Chengxi Ye, Grace Chu, Yanfeng Liu +5
The discontinuous operations inherent in quantization and sparsification introduce a long-standing obstacle to backpropagation, particularly in ultra-low precision and sparse regim…
Unleashing the Potential of SAM2 for Biomedical Images and Videos: A Survey
Yichi Zhang, Zhenrong Shen
The unprecedented developments in segmentation foundational models have become a dominant force in the field of computer vision, introducing a multitude of previously unexplored ca…
Mamba-UNet: UNet-Like Pure Visual Mamba for Medical Image Segmentation
Ziyang Wang, Jian-Qing Zheng, Yichi Zhang +2
In recent advancements in medical image analysis, Convolutional Neural Networks (CNN) and Vision Transformers (ViT) have set significant benchmarks. While the former excels in capt…
Trainable Fixed-Point Quantization for Deep Learning Acceleration on FPGAs
Dingyi Dai, Yichi Zhang, Jiahao Zhang +4
Quantization is a crucial technique for deploying deep learning models on resource-constrained devices, such as embedded FPGAs. Prior efforts mostly focus on quantizing matrix mult…