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

Ostrich

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.

EXPEL

讽刺滑稽戏剧

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.

脱毛

Flatter

Evocative

思想

同谋

模仿

enmesh

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