arXiv AI By Konstantinos Moutselos, Ilias Maglogiannis

Reliable Benchmarking of Artifact Detection in Computational Pathology: A Reproducibility and Uncertainty Analysis

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arXiv Machine Learning
Aug 5

Assessment of Conditional Diffusion Model for Synthetic Histopathology Image Generation

arXiv:2608. 03990v1 Announce Type: new Abstract: Synthetic histopathology image generation has emerged as an approach that may address data scarcity in computational pathology, yet current evaluation methodologies may not fully assess synthetic data quality for medical applications.

By Seyed Kahaki, Shijie Li, Weijie Chen, Nicholas Petrick
arXiv Machine Learning
Aug 27

CropCop: An Auditable 120-Class Plant-Health Model from Benchmark Reconstruction to a Quantised Runtime Artifact

CropCop is a closed‑set plant‑health recognition system covering 120 operational classes, built from a rigorously audited dataset of 109,107 images after removing 3,233 duplicate relationships. The model, based on a fine‑tuned DINOv3 ConvNeXt‑Tiny, achieves 98.51% accuracy and 96.87% macro‑F1 on a locked internal test, while a quantised MobileNetV4 variant reaches 98.46% accuracy and 96.23% macro‑F1 in a 22.60 MiB runtime artifact. Validation‑only post‑training quantisation and a compact ExecuTorch/XNNPACK PTE ensure high fidelity between the trained model and its deployed form, with minimal decision changes between the INT8 graph and the final artifact.

By Rana Muhammad Ahmed, Sabahat Abbas
arXiv AI
Aug 5

A Deployment-Friendly Foundational Framework for Efficient Computational Pathology

arXiv:2602. 14010v2 Announce Type: replace-cross Abstract: Pathology foundation models (PFMs) generalize well across computational pathology tasks but remain costly for gigapixel whole-slide image analysis.

By Yu Cai, Cheng Jin, Zhengyu Zhang, Jiabo Ma, Fengtao Zhou, Yingxue Xu, Zhengrui Guo, Yihui Wang, Zhengyu Zhang, Ling Liang, Yonghao Tan, Pingcheng Dong, Du Cai, On Ki Tang, Chenglong Zhao, Zhijian Cen, Ying Tan, Xi Wang, Can Yang, Yali Xu, Jing Cui, Zhenhui Li, Ronald Cheong Kin Chan, Yueping Liu, Feng Gao, Xiuming Zhang, Li Liang, Hao Chen, Kwang-Ting Cheng