activity
20192022
most citedInstance Adaptive Self-Training for Unsupervised Domain Adaptation

19 citations · 26 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2022

TCNL: Transparent and Controllable Network Learning Via Embedding Human-Guided Concepts

Zhihao Wang, Chuang Zhu

Explaining deep learning models is of vital importance for understanding artificial intelligence systems, improving safety, and evaluating fairness. To better understand and contro…

eess.IV20222 cited

BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix

Shengjie Liu, Chuang Zhu, Feng Xu +3

The evaluation of human epidermal growth factor receptor 2 (HER2) expression is essential to formulate a precise treatment for breast cancer. The routine evaluation of HER2 is cond…

cs.CV20221 cited

Sample Prior Guided Robust Model Learning to Suppress Noisy Labels

Wenkai Chen, Chuang Zhu, Yi Chen +2

Imperfect labels are ubiquitous in real-world datasets and seriously harm the model performance. Several recent effective methods for handling noisy labels have two key steps: 1) d…

cs.CV2021

Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark

Shuhao Qiu, Chuang Zhu, Wenli Zhou

In recent years, deep learning-based methods have shown promising results in computer vision area. However, a common deep learning model requires a large amount of labeled data, wh…

cs.CV202019 cited

Instance Adaptive Self-Training for Unsupervised Domain Adaptation

Ke Mei, Chuang Zhu, Jiaqi Zou +1

The divergence between labeled training data and unlabeled testing data is a significant challenge for recent deep learning models. Unsupervised domain adaptation (UDA) attempts to…

eess.IV2020

Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet

Chuang Zhu, Ke Mei, Ting Peng +4

The automatic and objective medical diagnostic model can be valuable to achieve early cancer detection, and thus reducing the mortality rate. In this paper, we propose a highly eff…