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1 Ergebnisse
1
MoPE-CLIP: Structured Pruning for Efficient Vision-Language..:
, In:
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
,
Lin, Haokun
;
Bai, Haoli
;
Liu, Zhili
... - p. 27360-27370 , 2024
Link:
https://doi.org/10.1109/CVPR52733.2024.02584
RT T1 <cTitle>2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)</cTitle>: T1 <Title>MoPE-CLIP: Structured Pruning for Efficient Vision-Language Models with Module-Wise Pruning Error Metric</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10656104&Exemplar=1&LAN=DE A1 Lin, Haokun A1 Bai, Haoli A1 Liu, Zhili A1 Hou, Lu A1 Sun, Muyi A1 Song, Linqi A1 Wei, Ying A1 Surr, Zhenan YR 2024 SN 2575-7075 K1 Measurement K1 Computer vision K1 Costs K1 Computational modeling K1 Measurement uncertainty K1 Pattern recognition K1 Vision-Language Models K1 CLIP K1 Model Compression K1 Structured Pruning SP 27360 OP 27370 LK http://dx.doi.org/https://doi.org/10.1109/CVPR52733.2024.02584 DO https://doi.org/10.1109/CVPR52733.2024.02584 SF ELIB - SuUB Bremen
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