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Titlebook: Computer Vision in Control Systems—6; Advances in Practica Margarita N. Favorskaya,Lakhmi C Jain Book 2020 Springer Nature Switzerland AG 2

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21#
發(fā)表于 2025-3-25 07:18:48 | 只看該作者
22#
發(fā)表于 2025-3-25 09:05:37 | 只看該作者
Astronomy and Astrophysics Libraryon and graphical representation of the power spectrum and analyse how it influenced by the motion blur. Finally, we design a novel tool in a view of the vector field of the power spectrum for image and video sequences analysis.
23#
發(fā)表于 2025-3-25 11:57:12 | 只看該作者
The Design and Engineering of Curiosityning. The algorithm builds the path of the robot and map of the environment. The path of robot is already noisy. To overcome a noise influence, we add encoders, which describe the passable way of the robot.
24#
發(fā)表于 2025-3-25 19:20:27 | 只看該作者
25#
發(fā)表于 2025-3-25 23:31:33 | 只看該作者
The Object-Oriented Simultaneous Localization and Mapping on the Spherobot Platform,ning. The algorithm builds the path of the robot and map of the environment. The path of robot is already noisy. To overcome a noise influence, we add encoders, which describe the passable way of the robot.
26#
發(fā)表于 2025-3-26 03:09:09 | 只看該作者
Design Methods and Project Management,ubdue big output signal values are presented. Theoretical distributions of stable estimations are obtained. By means of statistical modeling, a coincidence between experimental and theoretical characteristics is established. The suggested algorithms are easy to calculate.
27#
發(fā)表于 2025-3-26 06:07:38 | 只看該作者
28#
發(fā)表于 2025-3-26 11:14:03 | 只看該作者
https://doi.org/10.1007/978-3-031-38168-3move the noise from scanned documents. This chapter discusses a possibility of using Local Binary Patterns (LBP) operator to make changes into the operation of Non-Local Means (NLM) noise reduction algorithm. As a result, it was possible to improve a quality of scanned images after their processing by the proposed modified algorithm.
29#
發(fā)表于 2025-3-26 14:37:49 | 只看該作者
30#
發(fā)表于 2025-3-26 16:49:31 | 只看該作者
Comparative Evaluation of Algorithms for Trajectory Filtering, allows to take into account the nature of the motion of the tracked object more fully. At the same time, it combines the simplicity of linear filtering with a separate estimation for each coordinate. Thus, it is more preferred for practical application.
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