多模态信息融合

Open datasets and machine learning for two-phase heat transfer: a review following a spatial-temporal taxonomy

用于多相输运和热系统数据驱动建模的开放多模态数据集与开源软件

Christy Dunlap, Ridwan Olabiyi, Firas Al-Hindawi, Hari Pandey, Stephen Pierson, Daniel Curl, Braden Stevens, Mohammad Ishraq Hossain, Annapurna Parjuli, Chinmaya Joshi, Ashif Iquebal, Han Hu

机构 * Department of Mechanical Engineering, University of Arkansas（阿肯色大学机械工程系） 纠错

专题命中 红外-可见光融合 ：multimodal fusion(abstract)

AI总结 本文介绍了一个由NED3实验室开发的开放多模态数据集和开源软件生态系统，提出了空间加时间维度（S+TD）分类框架，并重点描述了SeqReg序列回归库，以推动可复现的AI赋能热流体研究。

Comments Accepted manuscript replacing arXiv:2605.23037 (https://arxiv.org/abs/2605.23037) (v1). Substantially expanded from the original preprint and published in Transport Phenomena 2026, 1(3), 20260081. this https URL (https://doi.org/10.1515/tp-2026-0081)