5 papers · 1 filter
SpectralKAN: Weighted Activation Distribution Kolmogorov-Arnold Network for Hyperspectral Image Change Detection
Yanheng Wang, Xiaohan Yu, Yongsheng Gao +6
Kolmogorov-Arnold networks (KANs) represent data features by learning the activation functions and demonstrate superior accuracy with fewer parameters, FLOPs, GPU memory usage (Mem…
LGD: Leveraging Generative Descriptions for Zero-Shot Referring Image Segmentation
Jiachen Li, Qing Xie, Renshu Gu +3
Zero-shot referring image segmentation aims to locate and segment the target region based on a referring expression, with the primary challenge of aligning and matching semantics a…
Visual and Semantic Prompt Collaboration for Generalized Zero-Shot Learning
Huajie Jiang, Zhengxian Li, Xiaohan Yu +4
Generalized zero-shot learning aims to recognize both seen and unseen classes with the help of semantic information that is shared among different classes. It inevitably requires c…
Propensity-driven Uncertainty Learning for Sample Exploration in Source-Free Active Domain Adaptation
Zicheng Pan, Xiaohan Yu, Weichuan Zhang +1
Source-free active domain adaptation (SFADA) addresses the challenge of adapting a pre-trained model to new domains without access to source data while minimizing the need for targ…
EIANet: A Novel Domain Adaptation Approach to Maximize Class Distinction with Neural Collapse Principles
Zicheng Pan, Xiaohan Yu, Yongsheng Gao
Source-free domain adaptation (SFDA) aims to transfer knowledge from a labelled source domain to an unlabelled target domain. A major challenge in SFDA is deriving accurate categor…