4 papers
Disentangling Tabular Data Towards Better One-Class Anomaly Detection
Jianan Ye, Zhaorui Tan, Yijie Hu +3
Tabular anomaly detection under the one-class classification setting poses a significant challenge, as it involves accurately conceptualizing "normal" derived exclusively from a si…
Covariance-based Space Regularization for Few-shot Class Incremental Learning
Yijie Hu, Guanyu Yang, Zhaorui Tan +3
Few-shot Class Incremental Learning (FSCIL) presents a challenging yet realistic scenario, which requires the model to continually learn new classes with limited labeled data (i.e.…
MedMAP: Promoting Incomplete Multi-modal Brain Tumor Segmentation with Alignment
Tianyi Liu, Zhaorui Tan, Muyin Chen +3
Brain tumor segmentation is often based on multiple magnetic resonance imaging (MRI). However, in clinical practice, certain modalities of MRI may be missing, which presents a more…
Rethinking Information Loss in Medical Image Segmentation with Various-sized Targets
Tianyi Liu, Zhaorui Tan, Kaizhu Huang +1
Medical image segmentation presents the challenge of segmenting various-size targets, demanding the model to effectively capture both local and global information. Despite recent e…