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Dezhi Wu

2 accepted papers

2025

A Progressive Local Variance-guided Strategy for Improving Data Augmentation Reliability

ICASSP 2025accepted

Recently, CutMix-based augmentation has emerged as a promising strategy for providing regularization to deep neural networks. However, the randomness in cropping may result in uninformative or non-representative regions being selected, resulting in a synthesized image without the desired features. T…

Cited by 0SourceScholar
2025

NanoGen: A High-affinity Nanobody Generation Model with Guided Diffusion

ICASSP 2025accepted

Nanobodies are promising therapeutic agents due to their superior biological properties. Given the importance of binding affinity, a computational model capable of generating high-affinity nanobodies can significantly accelerate the design process. However, two key challenges remain: 1) integrating…

Cited by 0SourceScholar