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Xiaofeng Qu

2 accepted papers

2025

Learning Together Securely: Prototype-Based Federated Multi-Modal Hashing for Safe and Efficient Multi-Modal Retrieval

AAAI 2025technical

With the proliferation of multi-modal data, safe and efficient multi-modal hashing retrieval has become a pressing research challenge, particularly due to concerns over data privacy during centralized processing. To address this, we propose Prototype-based Federated Multi-modal Hashing (PFMH), an in…

2022

Pixel-Level and Affinity-Level Knowledge Distillation for Unsupervised Segmentation of Covid-19 Lesions

ICASSP 2022accepted

Automatic segmentation of COVID-19 lesions is essential for computer-aided diagnosis. However, this task remains challenging because widely-used supervised based methods require large-scale annotated data that is difficult to obtain. Although an unsupervised method based on anomaly detection has sho…

Cited by 0SourceScholar