173 citations · 256 across the 28 of their papers we have counts for
8 papers · 1 filter
VQA4CIR: Boosting Composed Image Retrieval with Visual Question Answering
Chun-Mei Feng, Yang Bai, Tao Luo +6
Albeit progress has been made in Composed Image Retrieval (CIR), we empirically find that a certain percentage of failure retrieval results are not consistent with their relative c…
Leveraging Anatomical Constraints with Uncertainty for Pneumothorax Segmentation
Han Yuan, Chuan Hong, Nguyen Tuan Anh Tran +2
Pneumothorax is a medical emergency caused by abnormal accumulation of air in the pleural space - the potential space between the lungs and chest wall. On 2D chest radiographs, pne…
Sentence-level Prompts Benefit Composed Image Retrieval
Yang Bai, Xinxing Xu, Yong Liu +5
Composed image retrieval (CIR) is the task of retrieving specific images by using a query that involves both a reference image and a relative caption. Most existing CIR models adop…
Uncertainty-inspired Open Set Learning for Retinal Anomaly Identification
Meng Wang, Tian Lin, Lianyu Wang +21
Failure to recognize samples from the classes unseen during training is a major limitation of artificial intelligence in the real-world implementation for recognition and classific…
Learning Federated Visual Prompt in Null Space for MRI Reconstruction
Chun-Mei Feng, Bangjun Li, Xinxing Xu +3
Federated Magnetic Resonance Imaging (MRI) reconstruction enables multiple hospitals to collaborate distributedly without aggregating local data, thereby protecting patient privacy…
Medical Phrase Grounding with Region-Phrase Context Contrastive Alignment
Zhihao Chen, Yang Zhou, Anh Tran +8
Medical phrase grounding (MPG) aims to locate the most relevant region in a medical image, given a phrase query describing certain medical findings, which is an important task for…
Federated Uncertainty-Aware Aggregation for Fundus Diabetic Retinopathy Staging
Meng Wang, Lianyu Wang, Xinxing Xu +5
Deep learning models have shown promising performance in the field of diabetic retinopathy (DR) staging. However, collaboratively training a DR staging model across multiple instit…
Reliable Federated Disentangling Network for Non-IID Domain Feature
Meng Wang, Kai Yu, Chun-Mei Feng +6
Federated learning (FL), as an effective decentralized distributed learning approach, enables multiple institutions to jointly train a model without sharing their local data. Howev…