88 citations · 231 across the 9 of their papers we have counts for
6 papers · 1 filter
Efficient Joint Optimization of Layer-Adaptive Weight Pruning in Deep Neural Networks
Kaixin Xu, Zhe Wang, Xue Geng +4
In this paper, we propose a novel layer-adaptive weight-pruning approach for Deep Neural Networks (DNNs) that addresses the challenge of optimizing the output distortion minimizati…
GaitFormer: Revisiting Intrinsic Periodicity for Gait Recognition
Qian Wu, Ruixuan Xiao, Kaixin Xu +3
Gait recognition aims to distinguish different walking patterns by analyzing video-level human silhouettes, rather than relying on appearance information. Previous research on gait…
MetaGrad: Adaptive Gradient Quantization with Hypernetworks
Kaixin Xu, Alina Hui Xiu Lee, Ziyuan Zhao +3
A popular track of network compression approach is Quantization aware Training (QAT), which accelerates the forward pass during the neural network training and inference. However,…
Object-Aware Self-supervised Multi-Label Learning
Xu Kaixin, Liu Liyang, Zhao Ziyuan +2
Multi-label Learning on Image data has been widely exploited with deep learning models. However, supervised training on deep CNN models often cannot discover sufficient discriminat…
Hierarchical Consistency Regularized Mean Teacher for Semi-supervised 3D Left Atrium Segmentation
Shumeng Li, Ziyuan Zhao, Kaixin Xu +2
Deep learning has achieved promising segmentation performance on 3D left atrium MR images. However, annotations for segmentation tasks are expensive, costly and difficult to obtain…
DSAL: Deeply Supervised Active Learning from Strong and Weak Labelers for Biomedical Image Segmentation
Ziyuan Zhao, Zeng Zeng, Kaixin Xu +2
Image segmentation is one of the most essential biomedical image processing problems for different imaging modalities, including microscopy and X-ray in the Internet-of-Medical-Thi…