Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Ruibo Gao"'
Publikováno v:
Systems Science & Control Engineering, Vol 12, Iss 1 (2024)
Improving the effectiveness of harvesting robots requires quick and accurate apple detection in natural environments. The colour and shape features of apples are corrupted due to the reflected light and the incomplete coverage of the fruit bag, bring
Externí odkaz:
https://doaj.org/article/a8536e456a4e4c9cb6ec7a6544f69cec
Publikováno v:
Systems Science & Control Engineering, Vol 12, Iss 1 (2024)
Grape cluster detection is a crucial step in the visual tasks of automated grape harvesting. Background and occlusion lead to difficulty in detecting grape clusters under natural environments. Some improvements have been proposed to solve this issue.
Externí odkaz:
https://doaj.org/article/1d5b39bbf71249079eeedaa8fc430f9a
Publikováno v:
Alexandria Engineering Journal, Vol 94, Iss , Pp 274-286 (2024)
In this paper, we consider the evolution of a new probability distribution called the exponential flexible Weibull distribution. The proposed exponential flexible Weibull distribution is obtained by combining the flexible Weibull extension with the e
Externí odkaz:
https://doaj.org/article/5527ba3f64c2477f8900686c341067a9
Autor:
Meiyu Qu, Qiangqiang He, Jiahao Luo, Tingyu Shen, Ruibo Gao, Yana Xu, Chengyun Xu, Muhammad Qasim Barkat, Ling-Hui Zeng, Ximei Wu
Publikováno v:
Genes and Diseases, Vol 10, Iss 5, Pp 2013-2028 (2023)
Alternative splicing (AS) produces the different mRNA splicing bodies, which are then translated into multiple protein isoforms and participate in various biological functions. With a deeper understanding of alternative splicing through the study of
Externí odkaz:
https://doaj.org/article/09a4b59300c64a4b9ca6e66ec08ced05
Publikováno v:
Agriculture, Vol 13, Iss 8, p 1513 (2023)
Accurate semantic segmentation of disease spots is critical in the evaluation and treatment of cucumber leaf damage. To solve the problem of poor segmentation accuracy caused by the imbalanced feature fusion of SegFormer, the Efficient Channel Attent
Externí odkaz:
https://doaj.org/article/3ef0c841d40a4ab49f84f88d5dfbe7ea
Publikováno v:
Insects, Vol 14, Iss 4, p 388 (2023)
Pyrethroid resistance of thrips has been reported in many countries, and knockdown resistance (kdr) has been identified as a main mechanism against pyrethroids in many insects. To characterize pyrethroid resistance in Megalurothrips usitatus from the
Externí odkaz:
https://doaj.org/article/7b3ca9f5f767458891f0094384064d87
Publikováno v:
IEEE Access, Vol 8, Pp 189869-189877 (2020)
RNA plays an important role in many biological processes, and RNA functions are primarily achieved by binding with a variety of proteins. But with the increasing complexity of RPIs networks, high-throughput biological techniques are usually expensive
Externí odkaz:
https://doaj.org/article/a0e48bc422844323b6bfafdd320e68bb
Autor:
Kaiyang Liu, Shuyue Ma, Kun Zhang, Ruibo Gao, Haifeng Jin, Peng Cao, Zhiguang Yuchi, Shaoying Wu
Publikováno v:
Journal of Agricultural and Food Chemistry. 71:2734-2744
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d39a53645e0702713fbc0faca7eca4d5
https://doi.org/10.1021/acs.jafc.2c05625
https://doi.org/10.1021/acs.jafc.2c05625
Autor:
Meiyu Qu, Qiangqiang He, Jiahao Luo, Tingyu Shen, Ruibo Gao, Yana Xu, Chengyun Xu, Muhammad Qasim Barkat, Ling-Hui Zeng, Ximei Wu
Publikováno v:
Genes & Diseases.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b560da9acbd15503d7e89265f92d12a
https://doi.org/10.1016/j.gendis.2022.10.014
https://doi.org/10.1016/j.gendis.2022.10.014
Recurrent geometric network(RGN) as a deep learning model have been successfully applied to predict protein 3D structure and achieved better results than conventional methods. However, because of the inter- nal complexity and nonlinear structure of d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2602ecfd08d8e7e71600e05ac851b701
https://doi.org/10.21203/rs.3.rs-2206279/v1
https://doi.org/10.21203/rs.3.rs-2206279/v1
