2 citations · 2 across the 4 of their papers we have counts for
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Adaptive receptive field-based spatial-frequency feature reconstruction network for fine-grained few-shot image classification
Linyue Zhang, Wenyi Zeng, Zicheng Pan +6
Feature reconstruction techniques are widely applied for few-shot fine-grained image classification (FSFGIC). Our research indicates that one of the main challenges facing existing…
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…
Mask-Guided Feature Extraction and Augmentation for Ultra-Fine-Grained Visual Categorization
Zicheng Pan, Xiaohan Yu, Miaohua Zhang +1
While the fine-grained visual categorization (FGVC) problems have been greatly developed in the past years, the Ultra-fine-grained visual categorization (Ultra-FGVC) problems have…