2 citations · 2 across the 4 of their papers we have counts for
6 papers · 1 filter
WBCAtt+: Fine-Grained Pixel-Level Morphological Annotations for White Blood Cell Images
Satoshi Tsutsui, Winnie Pang, Shuting He +1
The microscopic examination of white blood cells (WBCs) plays a fundamental role in pathology and is essential for diagnosing blood disorders such as leukemia and anemia. To suppor…
Digital Staining with Knowledge Distillation: A Unified Framework for Unpaired and Paired-But-Misaligned Data
Ziwang Xu, Lanqing Guo, Satoshi Tsutsui +3
Staining is essential in cell imaging and medical diagnostics but poses significant challenges, including high cost, time consumption, labor intensity, and irreversible tissue alte…
Towards Robust and Reliable Concept Representations: Reliability-Enhanced Concept Embedding Model
Yuxuan Cai, Xiyu Wang, Satoshi Tsutsui +2
Concept Bottleneck Models (CBMs) aim to enhance interpretability by predicting human-understandable concepts as intermediates for decision-making. However, these models often face…
Discovering Hidden Visual Concepts Beyond Linguistic Input in Infant Learning
Xueyi Ke, Satoshi Tsutsui, Yayun Zhang +1
Infants develop complex visual understanding rapidly, even preceding the acquisition of linguistic skills. As computer vision seeks to replicate the human vision system, understand…
Integrating Clinical Knowledge into Concept Bottleneck Models
Winnie Pang, Xueyi Ke, Satoshi Tsutsui +1
Concept bottleneck models (CBMs), which predict human-interpretable concepts (e.g., nucleus shapes in cell images) before predicting the final output (e.g., cell type), provide ins…
Evolving Storytelling: Benchmarks and Methods for New Character Customization with Diffusion Models
Xiyu Wang, Yufei Wang, Satoshi Tsutsui +3
Diffusion-based models for story visualization have shown promise in generating content-coherent images for storytelling tasks. However, how to effectively integrate new characters…