most citedCross-Field Transformer for Diabetic Retinopathy Grading on Two-field Fundus Images

2 citations · 6 across the 5 of their papers we have counts for

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5 papers

eess.IV2022

Boosting COVID-19 Severity Detection with Infection-aware Contrastive Mixup Classification

Junlin Hou, Jilan Xu, Nan Zhang +3

This paper presents our solution for the 2nd COVID-19 Severity Detection Competition. This task aims to distinguish the Mild, Moderate, Severe, and Critical grades in COVID-19 ches…

cs.CV20222 cited

Cross-Field Transformer for Diabetic Retinopathy Grading on Two-field Fundus Images

Junlin Hou, Jilan Xu, Fan Xiao +6

Automatic diabetic retinopathy (DR) grading based on fundus photography has been widely explored to benefit the routine screening and early treatment. Existing researches generally…

eess.IV2022

CMC v2: Towards More Accurate COVID-19 Detection with Discriminative Video Priors

Junlin Hou, Jilan Xu, Nan Zhang +4

This paper presents our solution for the 2nd COVID-19 Competition, occurring in the framework of the AIMIA Workshop at the European Conference on Computer Vision (ECCV 2022). In ou…

eess.IV20222 cited

Deep-OCTA: Ensemble Deep Learning Approaches for Diabetic Retinopathy Analysis on OCTA Images

Junlin Hou, Fan Xiao, Jilan Xu +3

The ultra-wide optical coherence tomography angiography (OCTA) has become an important imaging modality in diabetic retinopathy (DR) diagnosis. However, there are few researches fo…

cs.CV20222 cited

CREAM: Weakly Supervised Object Localization via Class RE-Activation Mapping

Jilan Xu, Junlin Hou, Yuejie Zhang +5

Weakly Supervised Object Localization (WSOL) aims to localize objects with image-level supervision. Existing works mainly rely on Class Activation Mapping (CAM) derived from a clas…