Analysis of different <i>p</i><sub>0</sub> values on DukeMTMCTOMarket1501 task.

Analysis of different <i>p</i><sub>0</sub> values on DukeMTMCTOMarket1501 task.

<p>Analysis of different <i>p</i><sub>0</sub> values on DukeMTMCTOMarket1501 task.</p>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Xuemei Bai (169120) (author)
مؤلفون آخرون:	Yuqing Zhang (32031) (author), Chenjie Zhang (11328211) (author), Zhijun Wang (31218) (author)
منشور في:	2025
الموضوعات:	Neuroscience Space Science Biological Sciences not elsewhere classified mean average precision innovative loss function target domains makes scale public datasets effective technical support domain migration performance 9 %, respectively model extremely challenging limited model performance unsupervised domain adaptation label noise processing label generated noise xlink "> person contrast learning technique unsupervised domain adapted identification </ p existing uda methods unsupervised domain label noise target domain contrast learning public safety label refinement effective way domain difference model training two large training process thereby enhancing still significant probabilistic uncertainty paper provides paper proposes negative impact method experiments many applications labeled data intelligent surveillance identification task good solution generation process generalization ability first enhance feature space feature representation experimental validation 4 %, 1 accuracy
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