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University of Oxford(牛津大学)

2026-06-19 至 2026-06-19 共收录 4
2606.20449 2026-06-19 cs.CV 新提交

InfantFace: Detecting infant faces in neonatal clinical environments

InfantFace:新生儿临床环境中的婴儿面部检测

Abdullah Bin-Obaid, Maria M. Cobo, Rebeccah Slater, Lionel Tarassenko, Mauricio Villarroel

机构 * Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford(牛津大学生物医学工程研究所、工程科学系) Department of Paediatrics, University of Oxford(牛津大学儿科系) Universidad San Francisco de Quito USFQ, Colegio de Ciencias Biologicas y Ambientales(奎托大学圣弗朗西斯科德奎托大学,生物科学与环境学院)

AI总结 针对新生儿临床环境中的遮挡和光照问题,提出基于YOLOv11m的单阶段面部检测模型,在多个公开数据集预训练后,通过临床数据微调,AP50从0.87提升至0.96。

Comments 32 pages, 7 figures, 4 tables; supplementary information included

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2606.19390 2026-06-19 cs.SE cs.AI 新提交

Execution-bound advisory automation for agentic AI: a reproducible AIBOM-driven CSAF-VEX framework

面向执行约束的自主AI自动化:一种可复现的AIBOM驱动的CSAF-VEX框架

Petar Radanliev, Omar Santos, Carsten Maple, Kay Atefi

机构 * University of Oxford(牛津大学) Cisco Systems(思科系统) The Alan Turing Institute(艾伦·图灵研究所) University of Warwick – WMG(沃里克大学 – WMG) University of Hull(哈罗德大学)

AI总结 提出一种协议驱动框架,通过绑定SBOM和AIBOM工件与确定性环境捕获及结构化运行时遥测,结合静态与运行时证据生成CSAF VEX公告,经密码签名和确定性重放验证,在合成自主AI工作负载上评估。

Journal ref Execution-bound advisory automation for agentic AI: a reproducible AIBOM-driven CSAF-VEX framework. Front Artif Intell 9, (May 2026), 1826384

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2606.19539 2026-06-19 astro-ph.SR cs.AI 新提交

Review of Machine Learning Models for Solar Energetic Particle Prediction

太阳高能粒子预测的机器学习模型综述

Spiridon Kasapis, Pouya Hosseinzadeh, Kathryn Whitman, Ricky Egeland, Manolis Georgoulis, Angelos Vourlidas, Athanasios Papaioannou, Eleni Lavasa, Anastasios Anastasiadis, Giorgos Giannopoulos, Andres Munoz-Jaramillo, Bala Poduval, Irina N. Kitiashvili, Alexander G. Kosovichev, Viacheslav Sadykov, Soukaina Filali Boubrahimi, Tate T. Hutchins, Hameedullah A. Farooki, Manuel E. Cuesta, Leng Y. Khoo, Sungmin Pak, Robert Czarnota, Jamie S. Rankin, Jamey Szalay, Mitchell M. Shen, Georgios Livadiotis, Zigong Xu, David J. McComas, Nikolaos Sarlis, Dionissios Hristopulos, Arik Posner, Alec J. Engell, Mohammed AbuBakr Ali, Ali G. A. Abdelkawy, Abdelrazek M. K. Shaltout, M. M. Beheary, Christina O. Lee, Sigiava Aminalragia-Giamini, Constantinos Papadimitriou, Ingmar Sandberg, Savvas Raptis, Shah Muhammad Hamdi, Monica Laurenza, Mirko Stumpo, Sumanth A. Rotti, India Jackson, Aatiya Ali, Atilim Gunes Baydin, Nathan Schwadron, Subhamoy Chatterjee, Maher A. Dayeh, Gelu M. Nita, Patrick M. O'Keefe, Chun Jie Chong, Paul Kosovich, Russell D. Marroquin, Berkay Aydin, Petrus C. Martens, Lulu Zhao, Yang Chen, Yian Yu, Monica G. Bobra, Ward Manchester, Tamas Gombosi, Ming Zhang, Jesse Torres, Philip K. Chan, Mohamed Nedal, Kamen Kozarev, Peijin Zhang, Kimberly Moreland, Hazel M. Bain, Samuel Hart, Michael J. Starkey, Alan G. Ling, Simone Benella

机构 * Department of Astrophysical Sciences, Princeton University, Princeton, NJ, USA Computational Physics Branch, NASA Ames Research Center, Moffett Field, CA, USA Department of Computer Science, Utah State University, Logan, UT, USA Space Radiation Analysis Group, NASA Johnson Space Center, Houston, TX, USA Johns Hopkins Applied Physics Lab, 11100 Johns Hopkins Rd, Laurel, MD 20723, United States Research Center for Astronomy Applied Mathematics of the Academy of Athens, 4 Soranou Efesiou Street, Athens 11527, Greece Institute for Astronomy, Astrophysics, Space Applications Southwest Research Institute, Boulder, CO, USA Space Science Center, University of New Hampshire, Durham, NH, USA Department of Physics, New Jersey Institute of Technology, Newark, NJ, USA Astronomy Department, Georgia State University, Atlanta, GA, USA Department of Computer Science, Princeton University, Princeton, NJ, USA Department of Mathematics, Rowan University, Glassboro, NJ, USA Astronomy, California Institute of Technology, Pasadena, CA, USA Department of Physics, National Kapodistrian University of Athens, Athens, Greece School of Electrical Computer Engineering, Technical University of Crete, Chania, Greece Department of Astronomy Meteorology, Faculty of Science, Al-Azhar University, Cairo, Egypt Space Sciences Lab, University of California, Berkeley, CA, USA Research Consultancy, Athens, Greece Institute for Space Astrophysics Department of Physics Astronomy, Georgia State University, Atlanta, GA 30303, USA Aryabhatta Research Institute of Observational Sciences (ARIES), Manora Peak, Nainital-263001, Uttarakhand, India Department of Computer Science, Oxford University, Oxford, England Southwest Research Institute, San Antonio, TX, USA Computer Science Department, New Jersey Institute of Technology, Newark, NJ, USA Department of Physics, University of California San Diego, La Jolla, CA 92093, USA Department of Computer Science, Georgia State University, Atlanta, GA 30303, USA Department of Climate Engineering, University of Michigan, Ann Arbor, MI, USA Department of Statistics, University of Michigan, Ann Arbor, MI, USA Department of Electrical Engineering Computer Science, Florida Institute of Technology, Melbourne, FL, USA Astrophysics Section, School of Cosmic Physics, Dublin Institute for Advanced Studies, DIAS Dunsink Observatory, Dublin D15 XR2R, Ireland Institute of Astronomy of the Bulgarian Academy of Sciences, Sofia, Bulgaria Center for Solar-Terrestrial Research, New Jersey Institute of Technology, Newark, NJ 07102, USA Cooperative Programs for the Advancement of Earth System Science, University Corporation for Atmospheric Research, Boulder, CO, USA CIRES, University of Colorado Boulder, Boulder, CO, USA Space Weather Prediction Center, NOAA, Boulder, CO, USA Astronomy, College of Science, The University of Texas at San Antonio, San Antonio, TX, USA Space Weather Prediction Center, National Oceanic The University of Texas at San Antonio, San Antonio, TX, USA Environmental Research, Inc., MA, USA

AI总结 综述了用于太阳高能粒子预测的机器学习模型,包括数据集、架构、输入输出比较,并提出了未来研究建议。

Comments Review Paper, Maine text: 23 pages, References: 5 pages, Appendix: 42 pages

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2606.15015 2026-06-19 cs.CV cs.AI 新提交

NEXUS: Neural Energy Fields for Physically Consistent Contact-Rich 3D Object Dynamics

NEXUS: 用于物理一致的高接触3D物体动力学的神经能量场

Qizhen Ying, Guangming Wang, Yangchen Pan, Victor Adrian Prisacariu, Brian Sheil, Yixiong Jing

机构 * University of Oxford(牛津大学) University of Cambridge(剑桥大学)

AI总结 提出神经能量场框架NEXUS,通过标量能量和耗散项建模保守与非保守动力学,提升高接触3D场景下的长时程轨迹精度并指导视频生成。

Comments 18 pages, 4 figures, 6 tables. Preprint

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