Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Du, Chaoqun"'
Test-Time Adaptation (TTA) aims to adapt pre-trained models to the target domain during testing. In reality, this adaptability can be influenced by multiple factors. Researchers have identified various challenging scenarios and developed diverse meth
Externí odkaz:
http://arxiv.org/abs/2407.20080
Autor:
Guo, Jiayi, Zhao, Junhao, Ge, Chunjiang, Du, Chaoqun, Ni, Zanlin, Song, Shiji, Shi, Humphrey, Huang, Gao
Test-time adaptation (TTA) aims to enhance the performance of source-domain pretrained models when tested on unknown shifted target domains. Traditional TTA methods primarily adapt model weights based on target data streams, making model performance
Externí odkaz:
http://arxiv.org/abs/2406.04295
Long-tailed distributions frequently emerge in real-world data, where a large number of minority categories contain a limited number of samples. Such imbalance issue considerably impairs the performance of standard supervised learning algorithms, whi
Externí odkaz:
http://arxiv.org/abs/2403.06726
Recent advancements in semi-supervised learning have focused on a more realistic yet challenging task: addressing imbalances in labeled data while the class distribution of unlabeled data remains both unknown and potentially mismatched. Current appro
Externí odkaz:
http://arxiv.org/abs/2402.13505
Publikováno v:
Open Chemistry, Vol 21, Iss 1, Pp 408-26 (2023)
In this study, a novel Ho(iii) coordination complex with the chemical composition of [Ho6(acac)4L4(CH3O)6]·xCH3OH (1) has been prepared via using a polydentate Schiff base ligand N′-(2,3-dihydroxybenzylidene) picolinohydrazide (H2L) and a β-diket
Externí odkaz:
https://doaj.org/article/b64073b55a0042d6ac913e4669c1f912
Assessing the performance of Generative Adversarial Networks (GANs) has been an important topic due to its practical significance. Although several evaluation metrics have been proposed, they generally assess the quality of the whole generated image
Externí odkaz:
http://arxiv.org/abs/2112.04163
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Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:753-761
Assessing the performance of Generative Adversarial Networks (GANs) has been an important topic due to its practical significance. Although several evaluation metrics have been proposed, they generally assess the quality of the whole generated image
Autor:
Huang, Gao1 (AUTHOR) gaohuang@tsinghua.edu.cn, Du, Chaoqun1 (AUTHOR) dcq20@mails.tsinghua.edu.cn
Publikováno v:
IEEE Transactions on Systems, Man & Cybernetics. Systems. Dec2022, Vol. 52 Issue 12, Part 1, p7561-7573. 13p.
Akademický článek
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