Author

Shuo Jiang

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#artificial intelligence Mar 2026

EReCu: Pseudo-label Evolution Fusion and Refinement with Multi-Cue Learning for Unsupervised Camouflage Detection

This work proposes a unified UCOD framework that enhances both the reliability of pseudo-labels and the fidelity of features, and introduces the Multi-Cue Native Perception module, which extracts intrinsic visual priors by integrating low-level texture cues with mid-level semantics.

Shuo Jiang, Gaojian Zhang, Mingxue Tan et al. · arXiv.org · 0 citations

#artificial intelligence Open access Apr 2025

Towards Accurate and Lightweight Peripheral Neuroblastic Tumor Diagnosis via Contrastive Multi-scale Pathological Image Analysis.

Experimental results show that CoPath achieves competitive or superior performance compared with general image classifiers, pathology foundation models under linear probing, and pathology specific classification models, while maintaining substantially lower computational complexity.

Zhu Zhu, Shuo Jiang, Jin Zheng et al. · IEEE journal of biomedical a... · 0 citations