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Titlebook: Advances in Computational Vision and Robotics; Proceedings of the I George A. Tsihrintzis,Margarita N. Favorskaya,Srik Conference proceedin

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发表于 2025-3-21 16:30:00 | 显示全部楼层 |阅读模式
期刊全称Advances in Computational Vision and Robotics
期刊简称Proceedings of the I
影响因子2023George A. Tsihrintzis,Margarita N. Favorskaya,Srik
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发行地址Presents recent research in Computational Vision and Robotics.Proceedings of International Conference on Computational Vision and Robotics.Written by experts in the field
学科分类Learning and Analytics in Intelligent Systems
图书封面Titlebook: Advances in Computational Vision and Robotics; Proceedings of the I George A. Tsihrintzis,Margarita N. Favorskaya,Srik Conference proceedin
影响因子.Advances in Computational Vision and Robotics contains research papers from diverse field of engineering, computer science, social and bio-medical science. This book contains various research articles from the following domain:.i. Pattern recognition and Robotic Vision..ii. Artificial Intelligence and Deep Learning application..iii. Big Data Application in Robotics..iv. Deep Learning and Neural Network..Authors from the area of Particle Swarm Optimization, Defect Detection, Gesture Information Collection, Image Processing and Remote Sensing, Melody Recognition, Convolution Neural Network and Satellite Image processing etc. have contributed their research outcomes..
Pindex Conference proceedings 2023
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Conference proceedings 2023timization, Defect Detection, Gesture Information Collection, Image Processing and Remote Sensing, Melody Recognition, Convolution Neural Network and Satellite Image processing etc. have contributed their research outcomes..
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2662-3447 the area of Particle Swarm Optimization, Defect Detection, Gesture Information Collection, Image Processing and Remote Sensing, Melody Recognition, Convolution Neural Network and Satellite Image processing etc. have contributed their research outcomes..978-3-031-38653-4978-3-031-38651-0Series ISSN 2662-3447 Series E-ISSN 2662-3455
发表于 2025-3-22 14:00:51 | 显示全部楼层
Citizenship and Negotiated Spaces,he test set and 95.78% on the experimental set. Compared with the traditional composition method based on notes, the composition based on HMM can improve the logical rigor and aesthetic feeling of melody, and can provide algorithm support for the construction of piano automatic accompaniment system.
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Manfred Bornhofen,Martin C. Bornhofen convergence error of this algorithm are obviously lower than those of the contrast algorithm. The algorithm in this paper converges quickly and has high registration accuracy when the overlap rate is low and the initial position is quite different, which proves the robustness of the algorithm in this paper.
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Book Proposition and Unique Selling Pointso of the reconstructed signal is 18.312 and the correlation coefficient with the original signal is 0.9612. In addition, the moisture in oil is simply evaluated by using the reconstructed signal. The results show that the detection accuracy of moisture in oil based on reconstructed signal is 3% higher than that based on original signal.
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