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1 Ergebnisse
1
Asymmetric Loss For Multi-Label Classification:
, In:
2021 IEEE/CVF International Conference on Computer Vision (ICCV)
,
Ridnik, Tal
;
Ben-Baruch, Emanuel
;
Zamir, Nadav
... - p. 82-91 , 2021
Link:
https://doi.org/10.1109/ICCV48922.2021.00015
RT T1 <cTitle>2021 IEEE/CVF International Conference on Computer Vision (ICCV)</cTitle>: T1 <Title>Asymmetric Loss For Multi-Label Classification</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9710171&Exemplar=1&LAN=DE A1 Ridnik, Tal A1 Ben-Baruch, Emanuel A1 Zamir, Nadav A1 Noy, Asaf A1 Friedman, Itamar A1 Protter, Matan A1 Zelnik-Manor, Lihi YR 2021 SN 2380-7504 K1 Training K1 Computer vision K1 Adaptive systems K1 Object detection K1 Benchmark testing K1 Complexity theory K1 Task analysis K1 Recognition and classification; Efficient training and inference methods; Machine learning architectures and formulations; Optimization and learning methods; Scene analysis and understanding SP 82 OP 91 LK http://dx.doi.org/https://doi.org/10.1109/ICCV48922.2021.00015 DO https://doi.org/10.1109/ICCV48922.2021.00015 SF ELIB - SuUB Bremen
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