2 citations · 2 across the 6 of their papers we have counts for
6 papers
Intensive Vision-guided Network for Radiology Report Generation
Fudan Zheng, Mengfei Li, Ying Wang +5
Automatic radiology report generation is booming due to its huge application potential for the healthcare industry. However, existing computer vision and natural language processin…
Classifier-head Informed Feature Masking and Prototype-based Logit Smoothing for Out-of-Distribution Detection
Zhuohao Sun, Yiqiao Qiu, Zhijun Tan +2
Out-of-distribution (OOD) detection is essential when deploying neural networks in the real world. One main challenge is that neural networks often make overconfident predictions o…
Class Attention to Regions of Lesion for Imbalanced Medical Image Recognition
Jia-Xin Zhuang, Jiabin Cai, Jianguo Zhang +2
Automated medical image classification is the key component in intelligent diagnosis systems. However, most medical image datasets contain plenty of samples of common diseases and…
Adaptively Integrated Knowledge Distillation and Prediction Uncertainty for Continual Learning
Kanghao Chen, Sijia Liu, Ruixuan Wang +1
Current deep learning models often suffer from catastrophic forgetting of old knowledge when continually learning new knowledge. Existing strategies to alleviate this issue often f…
Learning Discriminative Representation via Metric Learning for Imbalanced Medical Image Classification
Chenghua Zeng, Huijuan Lu, Kanghao Chen +2
Data imbalance between common and rare diseases during model training often causes intelligent diagnosis systems to have biased predictions towards common diseases. The state-of-th…
Task-oriented Self-supervised Learning for Anomaly Detection in Electroencephalography
Yaojia Zheng, Zhouwu Liu, Rong Mo +3
Accurate automated analysis of electroencephalography (EEG) would largely help clinicians effectively monitor and diagnose patients with various brain diseases. Compared to supervi…