Chenglu Zhu
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    • Task-specific fine-tuning via variational information bottleneck for weakly-supervised pathology whole slide image classification
    • Test-Time Training for Semantic Segmentation with Output Contrastive Loss
    • Unleashing the Power of Prompt-driven Nucleus Instance Segmentation
    • Automatic and accurate segmentation of peripherally inserted central catheter (PICC) from chest X-rays using multi-stage attention-guided learning
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    • Category Separation For Weakly Supervised Multi-Class Cell Counting
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    • Complex carotid artery segmentation in multi-contrast MR sequences by improved optimal surface graph cuts based on flow line learning
    • End-to-end cell recognition by point annotation
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    • Weakly supervised learning for cell recognition in immunohistochemical cytoplasm staining images
    • Cascaded residual U-net for fully automatic segmentation of 3D carotid artery in high-resolution multi-contrast MR images
    • Generalizing nucleus recognition model in multi-source ki67 immunohistochemistry stained images via domain-specific pruning
    • Automatic centerline extraction of cerebrovascular in 4D CTA based on tubular features
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Test-Time Training for Semantic Segmentation with Output Contrastive Loss

Jan 1, 2023ยท
Yunlong Zhang
,
Yuxuan Sun
,
Sunyi Zheng
,
Zhongyi Shui
,
Chenglu Zhu
,
Lin Yang
ยท 0 min read
Cite
Type
Journal article
Publication
arXiv preprint arXiv:2311.07877
Last updated on Jan 1, 2023
← Task-specific fine-tuning via variational information bottleneck for weakly-supervised pathology whole slide image classification Jan 1, 2023
Unleashing the Power of Prompt-driven Nucleus Instance Segmentation Jan 1, 2023 →

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