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20212026
most citedAI can evolve without labels: self-evolving vision transformer for chest X-ray diagnosis through knowledge distillation

79 citations · 185 across the 18 of their papers we have counts for

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5 papers · 1 filter

eess.IV2021★ 19 cited

Federated Split Vision Transformer for COVID-19 CXR Diagnosis using Task-Agnostic Training

Sangjoon Park, Gwanghyun Kim, Jeongsol Kim +2

Federated learning, which shares the weights of the neural network across clients, is gaining attention in the healthcare sector as it enables training on a large corpus of decentr…

cs.CV2021★ 39 cited

DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulation

Gwanghyun Kim, Taesung Kwon, Jong Chul Ye

Recently, GAN inversion methods combined with Contrastive Language-Image Pretraining (CLIP) enables zero-shot image manipulation guided by text prompts. However, their applications…

eess.IV2021★ 8 cited

Vision Transformer using Low-level Chest X-ray Feature Corpus for COVID-19 Diagnosis and Severity Quantification

Sangjoon Park, Gwanghyun Kim, Yujin Oh +6

Developing a robust algorithm to diagnose and quantify the severity of COVID-19 using Chest X-ray (CXR) requires a large number of well-curated COVID-19 datasets, which is difficul…

eess.IV2021★ 3 cited

Severity Quantification and Lesion Localization of COVID-19 on CXR using Vision Transformer

Gwanghyun Kim, Sangjoon Park, Yujin Oh +6

Under the global pandemic of COVID-19, building an automated framework that quantifies the severity of COVID-19 and localizes the relevant lesion on chest X-ray images has become i…

eess.IV2021★ 27 cited

Vision Transformer for COVID-19 CXR Diagnosis using Chest X-ray Feature Corpus

Sangjoon Park, Gwanghyun Kim, Yujin Oh +6

Under the global COVID-19 crisis, developing robust diagnosis algorithm for COVID-19 using CXR is hampered by the lack of the well-curated COVID-19 data set, although CXR data with…