代码大模型 / AI 编程

Enhancing Renal Tumor Malignancy Prediction: Deep Learning with Automatic 3D CT Organ Focused Attention

增强肾肿瘤恶性预测：基于自动3D CT器官聚焦注意力的深度学习

Zhengkang Fan, Chengkun Sun, Russell Terry, Jie Xu, Longin Jan Latecki

机构 * 1 Department of Health Outcomes \& Biomedical Informatics, University of Florida, Gainesville, FL, USA 2 Department of Urology, University of Florida, Gainesville, FL, USA 3 Department of Computer \& Information Sciences, Temple University, Philadelphia, PA, USA 纠错

专题命中 仓库级理解 ：repository(abstract)；分类 cs.AI

AI总结 本文提出一种无需手动分割的深度学习框架，利用器官聚焦注意力机制提升肾肿瘤恶性预测的准确性。

Comments 5 pages, 2 figures, Accepted at IEEE ISBI 2026

TokEye: Fast Signal Extraction for Fluctuating Time Series via Offline Self-Supervised Learning From Fusion Diagnostics to Bioacoustics

TokEye: 通过离线自监督学习快速提取波动时间序列信号：从融合诊断到生物声学

Nathaniel Chen, Kouroche Bouchiat, Peter Steiner, Andrew Rothstein, David Smith, Max Austin, Mike van Zeeland, Azarakhsh Jalalvand, Egemen Kolemen

专题命中 仓库级理解 ：repository(abstract)；分类 cs.AI

AI总结 TokEye通过离线自监督学习从多种传感器数据中快速提取波动时间序列信号，用于等离子体波动测量与实时控制。

D-FINE-seg: Object Detection and Instance Segmentation Framework with multi-backend deployment

D-FINE-seg：具有多后端部署的物体检测和实例分割框架

Argo Saakyan, Dmitry Solntsev

专题命中 仓库级理解 ：repository(abstract)

AI总结 D-FINE-seg通过轻量级掩码头和面向分割的训练方法，实现了在TACO数据集上优于YOLO26的F1分数，同时支持多后端部署。

Comments 6 pages, 4 figures, 5 tables