马赛克
发表于 2025-3-28 17:11:39
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控诉
发表于 2025-3-28 19:31:02
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Constant
发表于 2025-3-29 00:43:17
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scrutiny
发表于 2025-3-29 03:52:36
Heinz-Willi Goelden,Klaus Th. Hess,Martin Morlock,Klaus D. Schmidt,Klaus J. Schröterbeen achieved by state-of-the-art encoders, and such improvement is increasingly manifest with the increase of resolution. Furthermore, we evaluate state-of-the-art objective video quality assessment models, and our results show that the SSIMplus measure performs the best in predicting 4K subjective
BIAS
发表于 2025-3-29 10:57:51
Heinz-Willi Goelden,Klaus Th. Hess,Martin Morlock,Klaus D. Schmidt,Klaus J. Schrötersionality of the data. Accordingly, in this work, we propose a unified approach to fitting of smooth geometric manifolds, such as curves and surfaces, to point clouds. The proposed method is based on a level-set formulation, which leads to a simple and computationally efficient algorithm, the practi
动机
发表于 2025-3-29 13:17:54
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一致性
发表于 2025-3-29 18:38:54
Heinz-Willi Goelden,Klaus Th. Hess,Martin Morlock,Klaus D. Schmidt,Klaus J. Schrötering time on server 3.25. reaching to 27.77 fps and 1.75., respectively and decreases power consumption on the edge node by 1.45., while it deteriorates accuracy only 5.6% in respect to ResNet-50 single precision on the average for three different datasets. The code and pre-trained networks are publi
吹气
发表于 2025-3-29 22:14:33
Heinz-Willi Goelden,Klaus Th. Hess,Martin Morlock,Klaus D. Schmidt,Klaus J. Schrötertwork architecture complexity of a deep neural network, which is important for on-device edge operation. In what is one of the largest comparative analysis between deep neural networks in literature, the NetScore metric, the top-1 accuracy metric, and the popular information density metric were comp
CHOKE
发表于 2025-3-30 02:19:25
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febrile
发表于 2025-3-30 06:02:27
Heinz-Willi Goelden,Klaus Th. Hess,Martin Morlock,Klaus D. Schmidt,Klaus J. Schrötering time on server 3.25. reaching to 27.77 fps and 1.75., respectively and decreases power consumption on the edge node by 1.45., while it deteriorates accuracy only 5.6% in respect to ResNet-50 single precision on the average for three different datasets. The code and pre-trained networks are publi