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20172024
most citedCross-Modality Deep Feature Learning for Brain Tumor Segmentation

290 citations · 740 across the 30 of their papers we have counts for

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Showing 2022Show all

11 papers · 1 filter

cs.CV2022★ 7 cited

Compound Batch Normalization for Long-tailed Image Classification

Lechao Cheng, Chaowei Fang, Dingwen Zhang +2

Significant progress has been made in learning image classification neural networks under long-tail data distribution using robust training algorithms such as data re-sampling, re-…

cs.CV2022★ 1 cited

Combating Noisy Labels in Long-Tailed Image Classification

Chaowei Fang, Lechao Cheng, Huiyan Qi +1

Most existing methods that cope with noisy labels usually assume that the class distributions are well balanced, which has insufficient capacity to deal with the practical scenario…

eess.IV2022★ 1 cited

Deep 3D Vessel Segmentation based on Cross Transformer Network

Chengwei Pan, Baolian Qi, Gangming Zhao +4

The coronary microvascular disease poses a great threat to human health. Computer-aided analysis/diagnosis systems help physicians intervene in the disease at early stages, where 3…

cs.CV2022

Computer-aided Tuberculosis Diagnosis with Attribute Reasoning Assistance

Chengwei Pan, Gangming Zhao, Junjie Fang +6

Although deep learning algorithms have been intensively developed for computer-aided tuberculosis diagnosis (CTD), they mainly depend on carefully annotated datasets, leading to mu…

cs.CV2022★ 1 cited

Structured Attention Composition for Temporal Action Localization

Le Yang, Junwei Han, Tao Zhao +2

Temporal action localization aims at localizing action instances from untrimmed videos. Existing works have designed various effective modules to precisely localize action instance…

cs.CV2022★ 1 cited

Robust Single Image Dehazing Based on Consistent and Contrast-Assisted Reconstruction

De Cheng, Yan Li, Dingwen Zhang +3

Single image dehazing as a fundamental low-level vision task, is essential for the development of robust intelligent surveillance system. In this paper, we make an early effort to…