most citedLearning CNN on ViT: A Hybrid Model to Explicitly Class-specific Boundaries for Domain Adaptation

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cs.CV2025

DNA: Dual-branch Network with Adaptation for Open-Set Online Handwriting Generation

Tsai-Ling Huang, Nhat-Tuong Do-Tran, Ngoc-Hoang-Lam Le +2

Online handwriting generation (OHG) enhances handwriting recognition models by synthesizing diverse, human-like samples. However, existing OHG methods struggle to generate unseen c…

cs.CV2025

UI-Styler: Ultrasound Image Style Transfer with Class-Aware Prompts for Cross-Device Diagnosis Using a Frozen Black-Box Inference Network

Nhat-Tuong Do-Tran, Ngoc-Hoang-Lam Le, Ching-Chun Huang

The appearance of ultrasound images varies across acquisition devices, causing domain shifts that degrade the performance of fixed black-box downstream inference models when reused…

cs.CV2025

TRUST: Token-dRiven Ultrasound Style Transfer for Cross-Device Adaptation

Nhat-Tuong Do-Tran, Ngoc-Hoang-Lam Le, Ian Chiu +2

Ultrasound images acquired from different devices exhibit diverse styles, resulting in decreased performance of downstream tasks. To mitigate the style gap, unpaired image-to-image…

cs.CV2024★ 1 cited

HiGDA: Hierarchical Graph of Nodes to Learn Local-to-Global Topology for Semi-Supervised Domain Adaptation

Ba Hung Ngo, Doanh C. Bui, Nhat-Tuong Do-Tran +1

The enhanced representational power and broad applicability of deep learning models have attracted significant interest from the research community in recent years. However, these…

cs.CV2024★ 1 cited

Learning CNN on ViT: A Hybrid Model to Explicitly Class-specific Boundaries for Domain Adaptation

Ba Hung Ngo, Nhat-Tuong Do-Tran, Tuan-Ngoc Nguyen +2

Most domain adaptation (DA) methods are based on either a convolutional neural networks (CNNs) or a vision transformers (ViTs). They align the distribution differences between doma…