activity
20222024
most citedTPMIL: Trainable Prototype Enhanced Multiple Instance Learning for Whole Slide Image Classification

4 citations · 24 across the 19 of their papers we have counts for

collaborators

19 papers

eess.IV20241 cited

Discriminating retinal microvascular and neuronal differences related to migraines: Deep Learning based Crossectional Study

Feilong Tang, Matt Trinh, Annita Duong +5

Migraine, a prevalent neurological disorder, has been associated with various ocular manifestations suggestive of neuronal and microvascular deficits. However, there is limited und…

cs.CV2024

OphNet: A Large-Scale Video Benchmark for Ophthalmic Surgical Workflow Understanding

Ming Hu, Peng Xia, Lin Wang +11

Surgical scene perception via videos is critical for advancing robotic surgery, telesurgery, and AI-assisted surgery, particularly in ophthalmology. However, the scarcity of divers…

cs.CV2024

Generalizing to Unseen Domains in Diabetic Retinopathy with Disentangled Representations

Peng Xia, Ming Hu, Feilong Tang +6

Diabetic Retinopathy (DR), induced by diabetes, poses a significant risk of visual impairment. Accurate and effective grading of DR aids in the treatment of this condition. Yet exi…

cs.CV20242 cited

Diversified and Personalized Multi-rater Medical Image Segmentation

Yicheng Wu, Xiangde Luo, Zhe Xu +5

Annotation ambiguity due to inherent data uncertainties such as blurred boundaries in medical scans and different observer expertise and preferences has become a major obstacle for…

cs.CV20242 cited

EventRPG: Event Data Augmentation with Relevance Propagation Guidance

Mingyuan Sun, Donghao Zhang, Zongyuan Ge +4

Event camera, a novel bio-inspired vision sensor, has drawn a lot of attention for its low latency, low power consumption, and high dynamic range. Currently, overfitting remains a…

cs.CV20241 cited

Hunting Attributes: Context Prototype-Aware Learning for Weakly Supervised Semantic Segmentation

Feilong Tang, Zhongxing Xu, Zhaojun Qu +3

Recent weakly supervised semantic segmentation (WSSS) methods strive to incorporate contextual knowledge to improve the completeness of class activation maps (CAM). In this work, w…