activity
20202023
most citedHQG-Net: Unpaired Medical Image Enhancement with High-Quality Guidance

5 citations · 27 across the 14 of their papers we have counts for

collaborators

14 papers

cs.CV2023★ 2 cited

Semi-supervised Semantic Segmentation Meets Masked Modeling:Fine-grained Locality Learning Matters in Consistency Regularization

Wentao Pan, Zhe Xu, Jiangpeng Yan +4

Semi-supervised semantic segmentation aims to utilize limited labeled images and abundant unlabeled images to achieve label-efficient learning, wherein the weak-to-strong consisten…

eess.IV2023★ 5 cited

HQG-Net: Unpaired Medical Image Enhancement with High-Quality Guidance

Chunming He, Kai Li, Guoxia Xu +5

Unpaired Medical Image Enhancement (UMIE) aims to transform a low-quality (LQ) medical image into a high-quality (HQ) one without relying on paired images for training. While most…

cs.CV2022

Human-machine Interactive Tissue Prototype Learning for Label-efficient Histopathology Image Segmentation

Wentao Pan, Jiangpeng Yan, Hanbo Chen +4

Recently, deep neural networks have greatly advanced histopathology image segmentation but usually require abundant annotated data. However, due to the gigapixel scale of whole sli…

eess.IV2022★ 2 cited

Towards Better Dermoscopic Image Feature Representation Learning for Melanoma Classification

ChengHui Yu, MingKang Tang, ShengGe Yang +7

Deep learning-based melanoma classification with dermoscopic images has recently shown great potential in automatic early-stage melanoma diagnosis. However, limited by the signific…

eess.IV2022★ 1 cited

Seeking Common Ground While Reserving Differences: Multiple Anatomy Collaborative Framework for Undersampled MRI Reconstruction

Jiangpeng Yan, Chenghui Yu, Hanbo Chen +4

Recently, deep neural networks have greatly advanced undersampled Magnetic Resonance Image (MRI) reconstruction, wherein most studies follow the one-anatomy-one-network fashion, i.…

cs.LG2021★ 1 cited

Value Activation for Bias Alleviation: Generalized-activated Deep Double Deterministic Policy Gradients

Jiafei Lyu, Yu Yang, Jiangpeng Yan +1

It is vital to accurately estimate the value function in Deep Reinforcement Learning (DRL) such that the agent could execute proper actions instead of suboptimal ones. However, exi…