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Bo Zhang

5 papers hereh-index 9332 citations40 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author2

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • eess.IV1
same name
  • Bo Zhang — 51 papers, h 28
  • Bo Zhang — 36 papers, h 52
  • Bo Zhang — 29 papers, h 12
  • Bo Zhang — 28 papers, h 27
  • Bo Zhang — 23 papers, h 19
  • Bo Zhang — 22 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2025

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification

Yu Bai, Zitong Yu, Haowen Tian +11

We propose Spatial-Aware Correlated Multiple Instance Learning (SAC-MIL) for performing WSI classification. SAC-MIL consists of a positional encoding module to encode position info…

cs.CV2025

JanusNet: Hierarchical Slice-Block Shuffle and Displacement for Semi-Supervised 3D Multi-Organ Segmentation

Zheng Zhang, Tianzhuzi Tan, Guanchun Yin +2

Limited by the scarcity of training samples and annotations, weakly supervised medical image segmentation often employs data augmentation to increase data diversity, while randomly…

cs.CV2025

Contrastive Cross-Bag Augmentation for Multiple Instance Learning-based Whole Slide Image Classification

Bo Zhang, Xu Xinan, Shuo Yan +4

Recent pseudo-bag augmentation methods for Multiple Instance Learning (MIL)-based Whole Slide Image (WSI) classification sample instances from a limited number of bags, resulting i…

cs.CV2025

SSFMamba: Learning Symmetry-driven Spatial-Frequency Modeling for Physically Consistent 3D Medical Image Segmentation

Bo Zhang, Yifan Zhang, Shuo Yan +5

Accurate 3D medical image segmentation requires a delicate balance between fine-grained local details and global contextual understanding. While spatial-domain models often struggl…

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