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Zhen-Qiu Shu

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Sep 2026

Time–frequency feature-level independence contrastive learning with semantic consistency learning for mechanical fault diagnosis

In modern industrial systems, vibration signals acquired by sensors are frequently subject to varying degrees of distortion and degradation. Furthermore, the high cost of annotation in industrial settings leads to a severe scarcity of labeled fault samples. In recent years, self-supervised contrastive learning shows gr...

Zhen-Qiu Shu, Ting-Yong Chen, Da-Zheng Peng et al. · 0 citations
2026

Frequency-Aware Bias Calibration Attention Network for Hyperspectral Image Classification

Recently, self-attention mechanisms have significantly advanced hyperspectral image classification (HSIC) by enabling effective modeling of long-range spatial–spectral dependencies. However, existing methods often suffer from blurred land-cover boundaries and insufficient discriminability between spectrally similar cla...

Zhen-Qiu Shu, Nan-Bo Liu, Ke-Xin Zeng et al. · 0 citations
Conference Open access Sep 2026

Retrieval-Guided Completion Hashing with Token–Patch Alignment for Incomplete Cross-Modal Retrieval

Cross-modal hashing has been extensively adopted in cross-modal retrieval tasks owing to its high storage efficiency and fast retrieval capability. However, in practical applications, multimodal data often suffer from modality missing issues, which cause semantic incompleteness and thus severely impair both cross-modal...

Zhi-Xin Luo, Zhen-Qiu Shu · 0 citations
Sep 2026

scCGC2T: Curriculum-Guided Contrastive Co-Training Framework for scRNA-Seq Data Clustering.

Single-cell RNA sequencing (scRNA-seq) enables high-resolution analysis of cellular heterogeneity. Accurate scRNA-seq data clustering is crucial for cell type identification and subpopulation discovery. However, existing clustering methods are frequently affected by erroneous pseudo-labels generated through the static...

Zhen-Qiu Shu, R. Dong, Tianyang Xu et al. · 0 citations

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