From the 1 of 7 linked papers with an AI index.
7 papers
ProgFormer: Hierarchical Voxel Diffusion Transformer for Longitudinal Brain MRI Prediction
Dexuan Ding, Yuankai Qi, Luping Zhou +3
ProgFormer is a hierarchical diffusion transformer that predicts future brain MRI scans by first modeling coarse brain structure and then refining voxel-level details, using condit…
Teaching Prompts to Coordinate: Hierarchical Layer-Grouped Prompt Tuning for Continual Learning
Shengqin Jiang, Tianqi Kong, Yuankai Qi +5
Prompt-based continual learning methods fine-tune only a small set of additional learnable parameters while keeping the pre-trained model's parameters frozen. It enables efficient…
Unlocking Prototype Potential: An Efficient Tuning Framework for Few-Shot Class-Incremental Learning
Shengqin Jiang, Xiaoran Feng, Yuankai Qi +6
Few-shot class-incremental learning (FSCIL) seeks to continuously learn new classes from very limited samples while preserving previously acquired knowledge. Traditional methods of…
Multimodal Visual Surrogate Compression for Alzheimer's Disease Classification
Dexuan Ding, Ciyuan Peng, Endrowednes Kuantama +6
High-dimensional structural MRI (sMRI) images are widely used for Alzheimer's Disease (AD) diagnosis. Most existing methods for sMRI representation learning rely on 3D architecture…
Tracking the Unstable: Appearance-Guided Motion Modeling for Robust Multi-Object Tracking in UAV-Captured Videos
Jianbo Ma, Hui Luo, Qi Chen +5
Multi-object tracking (MOT) aims to track multiple objects while maintaining consistent identities across frames of a given video. In unmanned aerial vehicle (UAV) recorded videos,…
Adapter-Enhanced Semantic Prompting for Continual Learning
Baocai Yin, Ji Zhao, Huajie Jiang +5
Continual learning (CL) enables models to adapt to evolving data streams. A major challenge of CL is catastrophic forgetting, where new knowledge will overwrite previously acquired…