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Titlebook: Advances in Computational Science, Engineering and Information Technology; Proceedings of the T Dhinaharan Nagamalai,Ashok Kumar,Annamalai

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樓主: Waterproof
41#
發(fā)表于 2025-3-28 15:39:23 | 只看該作者
Generative AI Customer End Useses the traffic congestion, one of the largest metropolis problems, even more often to happen. To avoid this kind of issue, this paper proposes a management system by videomonitoring for the urban traffic. And the goal is to identify the vehicles e count them in period of time using Computer Vision and Image Processing techniques.
42#
發(fā)表于 2025-3-28 19:32:37 | 只看該作者
43#
發(fā)表于 2025-3-29 00:49:44 | 只看該作者
Generative AI Customer End Usesm side maximum a-posteriori (MAP) reconstruction is adopted with sub-pixel translational motion estimation algorithm for spatial resolution enhancement. Resulting algorithm is implemented in CUDA using a low end . 640 GPU, and an overall speed up of 10 – 11 times is achieved compared to ANSI C implementation running on a Core .5 CPU.
44#
發(fā)表于 2025-3-29 05:03:00 | 只看該作者
45#
發(fā)表于 2025-3-29 10:46:31 | 只看該作者
46#
發(fā)表于 2025-3-29 14:07:59 | 只看該作者
47#
發(fā)表于 2025-3-29 17:33:17 | 只看該作者
48#
發(fā)表于 2025-3-29 21:23:03 | 只看該作者
49#
發(fā)表于 2025-3-30 01:49:10 | 只看該作者
50#
發(fā)表于 2025-3-30 07:58:13 | 只看該作者
Generative AI Customer End Usescongestion). We propose to represent a traffic video shot by an interval valued features. Unlike the conventional methods, the interval valued feature representation is able to preserve the variations existing among the extracted features of a traffic video shot. Based on the proposed symbolic repre
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