250 citations · 340 across the 9 of their papers we have counts for
9 papers
Many-to-One Distribution Learning and K-Nearest Neighbor Smoothing for Thoracic Disease Identification
Yi Zhou, Lei Huang, Tianfei Zhou +1
Chest X-rays are an important and accessible clinical imaging tool for the detection of many thoracic diseases. Over the past decade, deep learning, with a focus on the convolution…
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration
Zhiqiang Shen, Zechun Liu, Jie Qin +3
Previous studies dominantly target at self-supervised learning on real-valued networks and have achieved many promising results. However, on the more challenging binary neural netw…
Slimmable Generative Adversarial Networks
Liang Hou, Zehuan Yuan, Lei Huang +3
Generative adversarial networks (GANs) have achieved remarkable progress in recent years, but the continuously growing scale of models makes them challenging to deploy widely in pr…
Normalization Techniques in Training DNNs: Methodology, Analysis and Application
Lei Huang, Jie Qin, Yi Zhou +3
Normalization techniques are essential for accelerating the training and improving the generalization of deep neural networks (DNNs), and have successfully been used in various app…
Group Whitening: Balancing Learning Efficiency and Representational Capacity
Lei Huang, Yi Zhou, Li Liu +2
Batch normalization (BN) is an important technique commonly incorporated into deep learning models to perform standardization within mini-batches. The merits of BN in improving a m…
A Benchmark for Studying Diabetic Retinopathy: Segmentation, Grading, and Transferability
Yi Zhou, Boyang Wang, Lei Huang +2
People with diabetes are at risk of developing an eye disease called diabetic retinopathy (DR). This disease occurs when high blood glucose levels cause damage to blood vessels in…
Invertible Zero-Shot Recognition Flows
Yuming Shen, Jie Qin, Lei Huang
Deep generative models have been successfully applied to Zero-Shot Learning (ZSL) recently. However, the underlying drawbacks of GANs and VAEs (e.g., the hardness of training with…
On the Number of Linear Regions of Convolutional Neural Networks
H. Xiong, L. Huang, M. Yu +3
One fundamental problem in deep learning is understanding the outstanding performance of deep Neural Networks (NNs) in practice. One explanation for the superiority of NNs is that…
Deformable Tube Network for Action Detection in Videos
Wei Li, Zehuan Yuan, Dashan Guo +3
We address the problem of spatio-temporal action detection in videos. Existing methods commonly either ignore temporal context in action recognition and localization, or lack the m…