6 papers
MEGA: Second-Order Gradient Alignment for Catastrophic Forgetting Mitigation in GFSCIL
Jinhui Pang, Changqing Lin, Hao Lin +4
Graph Few-Shot Class-Incremental Learning (GFSCIL) enables models to continually learn from limited samples of novel tasks after initial training on a large base dataset. Existing…
Synergistic Prompting for Robust Visual Recognition with Missing Modalities
Zhihui Zhang, Luanyuan Dai, Qika Lin +5
Large-scale multi-modal models have demonstrated remarkable performance across various visual recognition tasks by leveraging extensive paired multi-modal training data. However, i…
DWCL: Dual-Weighted Contrastive Learning for Multi-View Clustering
Hanning Yuan, Zhihui Zhang, Qi Guo +4
Multi-view contrastive clustering (MVCC) has gained significant attention for generating consistent clustering structures from multiple views through contrastive learning. However,…
A Hierarchical Reinforcement Learning Framework for Multi-UAV Combat Using Leader-Follower Strategy
Jinhui Pang, Jinglin He, Noureldin Mohamed Abdelaal Ahmed Mohamed +3
Multi-UAV air combat is a complex task involving multiple autonomous UAVs, an evolving field in both aerospace and artificial intelligence. This paper aims to enhance adversarial p…
ESC-MISR: Enhancing Spatial Correlations for Multi-Image Super-Resolution in Remote Sensing
Zhihui Zhang, Jinhui Pang, Jianan Li +1
Multi-Image Super-Resolution (MISR) is a crucial yet challenging research task in the remote sensing community. In this paper, we address the challenging task of Multi-Image Super-…
FTF-ER: Feature-Topology Fusion-Based Experience Replay Method for Continual Graph Learning
Jinhui Pang, Changqing Lin, Xiaoshuai Hao +5
Continual graph learning (CGL) is an important and challenging task that aims to extend static GNNs to dynamic task flow scenarios. As one of the mainstream CGL methods, the experi…