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of 655
pro vyhledávání: '"Cai Xi"'
In the realm of large-scale point cloud registration, designing a compact symbolic representation is crucial for efficiently processing vast amounts of data, ensuring registration robustness against significant viewpoint variations and occlusions. Th
Externí odkaz:
http://arxiv.org/abs/2412.02998
Autor:
Tsedendorj Bolorbat, Cao Jian En, Song Guo Dong, Batsuuri Ankhbayar, Guunii Lkhundev, Tsend Amgalantugs, Gonchig Batbold, Cao Peng, Cai Xi
Publikováno v:
Proceedings of the Mongolian Academy of Sciences, Pp 9-18 (2020)
In this article, we report artefacts found at the valley of Tsagaan Turuut River in the Khangai Mountain ranges in Central Mongolia. The artefacts were identified based upon core morphology, tool types and retouch. Regarding the core reduction techni
Externí odkaz:
https://doaj.org/article/a91aaf66ae7c4134b605dc55056620fc
Autor:
LUO Chenggang, DONG Shuang, ZHANG Jing, CAI Xi, OU Wuling, RAN Fengming, QIAN Yu, WANG Jun, HUANG Qing, HU Sheng
Publikováno v:
Zhongliu Fangzhi Yanjiu, Vol 47, Iss 4, Pp 227-234 (2020)
In the current pandemic of SARS-Cov-2 (formally known as novel coronavirus disease 2019, COVID-19), the cancer treatment is particularly a challenge that must be overcome as soon as possible. Currently, the clinical data on the prevalence of SARS-Cov
Externí odkaz:
https://doaj.org/article/79823a15e91d4f479636d83f5a7340ab
In unmanned aerial vehicle (UAV)-assisted orthogonal frequency division multiplexing (OFDM) systems, the potential advantage of the line-of-sight (LoS) path, characterized by its high probability of existence, has not been fully harnessed, thereby im
Externí odkaz:
http://arxiv.org/abs/2404.02162
Due to the implementation bottleneck of training data collection in realistic wireless communications systems, supervised learning-based timing synchronization (TS) is challenged by the incompleteness of training data. To tackle this bottleneck, we e
Externí odkaz:
http://arxiv.org/abs/2306.17570
Publikováno v:
Open Chemistry, Vol 6, Iss 2, Pp 188-198 (2008)
Externí odkaz:
https://doaj.org/article/9c06f9e6ef8646c8b2749b80c5e5d414
In this letter, a lightweight one-dimensional convolutional neural network (1-D CNN)-based timing synchronization (TS) method is proposed to reduce the computational complexity and processing delay and hold the timing accuracy in orthogonal frequency
Externí odkaz:
http://arxiv.org/abs/2209.06451
Publikováno v:
In Separation and Purification Technology 1 March 2024 331
Autor:
Cai, Xi1 (AUTHOR) cai_xi@ctg.com.cn, Yang, Zhangbin1 (AUTHOR) yang_zhangbin@ctg.com.cn, Liu, Pan1 (AUTHOR) liu_pan5@ctg.com.cn, Lian, Xueguang1 (AUTHOR) lian_xueguang@ctg.com.cn, Li, Zhuang2 (AUTHOR) 334881@whut.edu.cn, Zhu, Guorong2 (AUTHOR) zhgr_55@whut.edu.cn, Geng, Hua3 (AUTHOR) genghua@tsinghua.edu.cn
Publikováno v:
Energies (19961073). May2024, Vol. 17 Issue 9, p2220. 11p.
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