The TAB challenges provide the visual tracking community with a precisely defined and repeatable way of comparing short-term trackers as well as a common platform for discussing the evaluation and advancements made in the field of engineering thermal analysis.
The goal of the challenges is to build up a repository of considerable benchmarks and to organize workshops or similar events in order to push forward research in engineering thermal analysis.
Citing TAB
When using any of TAB benchmarks in your paper, please cite the TAB journal paper as well as the relevant papers describing the relevant benchmark.
Using TFRD benchmarks
@article{chen_hsld,
Author = {Xianqi Chen and Xiaoyu Zhao and Zhiqiang Gong and Jun Zhang and Xiaoqian Chen and Wen Yao},
Title = {A Deep Neural Network Surrogate Modeling Benchmark for Temperature Field Prediction of Heat Source Layout},
Journal = {Science China-Physics, Mechanics & Astronomy},
Year = {2021}
}
@article{zhao2021,
Author = {Xiaoyu Zhao and Zhiqiang Gong and Jun Zhang and Wen Yao and Xiaoqian Chen},
Title = {A surrogate model with data augmentation and deep transfer learning for temperature field prediction of heat source layout},
Journal = {Structural and Multidisciplinary Optimization},
Year = {2021}
}
Using HSLD benchmark
@article{gong_tfrd,
Author = {Xiaoqian Chen and Zhiqiang Gong and Xiaoyu Zhao and Weien Zhou and Wen Yao},
Title = {A Machine Learning Modelling Benchmark for Temperature Field Reconstruction of Heat-Source Systems},
Journal = {arXiv preprint arXiv:2108.08298},
Year = {2021}
}
@article{gong_pirl,
Author = {Zhiqiang Gong and Weien Zhou and Jun Zhang and Wei Peng and Wen Yao},
Title = {Physics-Informed Deep Reversible Regression Model for Temperature Field Reconstruction of Heat-Source Systems},
Journal = {arXiv preprint arXiv:2106.11929},
Year = {2021}
}
Highlights and news
Announcement
The CEC2022 HCLO challenge is over！