Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Baoxian Li"'
Autor:
Allen A. Zhang, Jing Shang, Baoxian Li, Bing Hui, Hongren Gong, Lin Li, You Zhan, Changfa Ai, Haoran Niu, Xu Chu, Zilong Nie, Zishuo Dong, Anzheng He, Hang Zhang, Dingfeng Wang, Yi Peng, Yifan Wei, Huixuan Cheng
Publikováno v:
Journal of Road Engineering, Vol 4, Iss 3, Pp 257-281 (2024)
Automated pavement condition survey is of critical importance to road network management. There are three primary tasks involved in pavement condition surveys, namely data collection, data processing and condition evaluation. Artificial intelligence
Externí odkaz:
https://doaj.org/article/dc14c30cd40c401ca638717f1f5fb2c5
Autor:
Baoxian LI, Guoliang LI, Haiqin YAO, Xin SHEN, Xiaoping LU, Zhourui LIANG, Fuli LIU, Pengyan ZHANG, Wenjun WANG
Publikováno v:
Progress in Fishery Sciences, Vol 44, Iss 2, Pp 118-126 (2023)
Macrocystis pyrifera is a large perennial brown alga used as a raw material in the chemical, energy, and medicine industries. It is also a high-quality material for the construction of seaweed beds with extremely high economic and ecological value. I
Externí odkaz:
https://doaj.org/article/5fed710720c7412bb3dfa3e8a2a00a6f
Publikováno v:
Ecological Indicators, Vol 150, Iss , Pp 110219- (2023)
Climate change is altering geographic and phylogeographic distribution of macroalgae, laying great impacts on their conservation and sustainable utilization. The potential distribution of two dominant cultured seaweeds-Neoporphyra haitanensis and Neo
Externí odkaz:
https://doaj.org/article/6b548ff7293e41de840ba8e1cc751d42
Publikováno v:
Journal of Advanced Transportation, Vol 2020 (2020)
Externí odkaz:
https://doaj.org/article/d035ca7b62054be9a5be88d69bc51427
Publikováno v:
Journal of Advanced Transportation, Vol 2019 (2019)
Pavement cracking is a significant symptom of pavement deterioration and deficiency. Conventional manual inspections of road condition are gradually replaced by novel automated inspection systems. As a result, a great amount of pavement surface infor
Externí odkaz:
https://doaj.org/article/94ecb9c8f4c84b888306041eb76bd590
Publikováno v:
Botanica Marina. 65:197-207
The purpose of this study was to develop stable microsatellite markers and evaluate the genetic background of cultivated Sargassum fusiforme. Based on the transcriptome data obtained by high-throughput sequencing, eleven polymorphic microsatellite ma
Autor:
Bing Wang, Yougen Huang, Daofeng Zhang, Hua Wang, Xiaopeng Zheng, Jingyuan Liu, Long Wang, Wenke Huang, Xingguan Chen, Weiwei Hu, Baoxian Liu, Mengqing He, Wenhua Zhou
Publikováno v:
Natural Gas Industry B, Vol 11, Iss 4, Pp 405-419 (2024)
Deep coalbed methane (CBM) has become one of the most significant potential sources of natural gas in China. However, the exploration and development of deep CBM in China is still in an initial stage, and its accumulation-forming characteristics requ
Externí odkaz:
https://doaj.org/article/6b5101493b2d439fb72aacbfa6adc0cd
Autor:
Rujie Jia, Wenjun Wang, Zhourui Liang, Xiaoping Lu, Haiqin Yao, Yi Liu, Baoxian Li, Citong Niu
Neopyropia yezoensis is a typical intertidal seaweed and a major mariculture crops in China. The culture area of N. yezoensis has been largely increasing in the past decade. Whether large-scale cultivation of N. yezoensis has a genetic impact on wild
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5106249f8488826d9caeff1f952bbc8f
https://doi.org/10.21203/rs.3.rs-1748442/v1
https://doi.org/10.21203/rs.3.rs-1748442/v1
Publikováno v:
Intelligent Transportation Infrastructure. 1
Cracks are an indicator for a bridge’s structural health and functional failures. Crack detection is one of the major tasks needed to maintain the structural health and serviceability of a bridge. At present, the most commonly used crack detection
Pixel-Level Cracking Detection on 3D Asphalt Pavement Images Through Deep-Learning- Based CrackNet-V
Autor:
Joshua Q. Li, Kelvin C. P. Wang, Baoxian Li, Yue Fei, Yang Liu, Allen Zhang, Guangwei Yang, Cheng Chen
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 21:273-284
A few recent developments have demonstrated that deep-learning-based solutions can outperform traditional algorithms for automated pavement crack detection. In this paper, an efficient deep network called CrackNet-V is proposed for automated pixel-le