most citedAccurate Image Restoration with Attention Retractable Transformer

47 citations · 88 across the 11 of their papers we have counts for

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cs.CV2023

HVTSurv: Hierarchical Vision Transformer for Patient-Level Survival Prediction from Whole Slide Image

Zhuchen Shao, Yang Chen, Hao Bian +3

Survival prediction based on whole slide images (WSIs) is a challenging task for patient-level multiple instance learning (MIL). Due to the vast amount of data for a patient (one o…

cs.CV2023★ 1 cited

CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

Simon Graham, Quoc Dang Vu, Mostafa Jahanifar +86

Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovatio…

cs.CV2022★ 47 cited

Accurate Image Restoration with Attention Retractable Transformer

Jiale Zhang, Yulun Zhang, Jinjin Gu +3

Recently, Transformer-based image restoration networks have achieved promising improvements over convolutional neural networks due to parameter-independent global interactions. To…

cs.CV2022★ 7 cited

Neuro-Symbolic Learning: Principles and Applications in Ophthalmology

Muhammad Hassan, Haifei Guan, Aikaterini Melliou +24

Neural networks have been rapidly expanding in recent years, with novel strategies and applications. However, challenges such as interpretability, explainability, robustness, safet…

cs.CV2022

Multiple Instance Learning with Mixed Supervision in Gleason Grading

Hao Bian, Zhuchen Shao, Yang Chen +4

With the development of computational pathology, deep learning methods for Gleason grading through whole slide images (WSIs) have excellent prospects. Since the size of WSIs is ext…