Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Xinwen Gao"'
Autor:
Hongping Song, Xinwen Gao, Liyun Song, Yubing Jiao, Lili Shen, Jinguang Yang, Changquan Li, Jun Shang, Hui Wang, Songbai Zhang, Ying Li
Publikováno v:
Frontiers in Genetics, Vol 14 (2024)
Potato virus Y (PVY) disease is a global problem that causes significant damage to crop quality and yield. As traditional chemical control methods are ineffective against PVY, it is crucial to explore new control strategies. MicroRNAs (miRNAs) play a
Externí odkaz:
https://doaj.org/article/4689f8971c7d44fa88ecc5d5b00c433b
Publikováno v:
Sensors, Vol 23, Iss 8, p 3910 (2023)
The detection of anomalies in multivariate time-series data is becoming increasingly important in the automated and continuous monitoring of complex systems and devices due to the rapid increase in data volume and dimension. To address this challenge
Externí odkaz:
https://doaj.org/article/0b9512072e204756a0d6b136128493ed
Publikováno v:
IEEE Access, Vol 7, Pp 107550-107559 (2019)
Automatic surveillance of abnormal events is a major unsolved problem in city management. By successful implementation of automatic surveillance of abnormal events, a significant amount of human resources in video monitoring can be economized. One so
Externí odkaz:
https://doaj.org/article/1854e88c501b408fa611202f5d65fdaf
Autor:
Xinwen Gao, Bairui Tong
Publikováno v:
Signal, Image and Video Processing. 17:2093-2100
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e4dbbb073cfa35da3032fa171b38681c
https://doi.org/10.1007/s11760-022-02423-9
https://doi.org/10.1007/s11760-022-02423-9
Autor:
Daojun Hu, Xinwen Gao
Publikováno v:
IEEE Sensors Journal. 21:27789-27800
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::823e86866f644a69888c406b4f8c7f61
https://doi.org/10.1109/jsen.2021.3124789
https://doi.org/10.1109/jsen.2021.3124789
Publikováno v:
SAE Technical Paper Series.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e1f19596a2f3ada4058e37a3eb61c06d
https://doi.org/10.4271/2022-01-1132
https://doi.org/10.4271/2022-01-1132
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 40:4453-4469
With the large-scale construction of urban subways, the detection of tunnel cracks becomes particularly important. Due to the complexity of the tunnel environment, it is difficult for traditional tunnel crack detection algorithms to detect and segmen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::84574063af35387153fa975853e8ae70
https://doi.org/10.3233/jifs-201296
https://doi.org/10.3233/jifs-201296
Autor:
Xinwen Gao, Bangyang Jin
Publikováno v:
2020 7th International Conference on Information Science and Control Engineering (ICISCE).
Aiming at the problems of low detection accuracy, small proportion of crack pixels in images and sensitivity to noise in highway pavement crack detection, an improved UNet model based on multi-scale and attention mechanism (UNet-MSAM) was proposed. I
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3d479e31ce72d41f81fc6eed9736a184
https://doi.org/10.1109/icisce50968.2020.00412
https://doi.org/10.1109/icisce50968.2020.00412
Publikováno v:
ICSAI
With the increase of tunnel operating pressure and the complex surrounding building structures, it is necessary to accurately, rapidly and automatically monitor the deformation of tunnels to ensure safe operation of subway trains. By taking into acco
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d817464a9d86943a30d3b3a76260309c
https://doi.org/10.1109/icsai48974.2019.9010527
https://doi.org/10.1109/icsai48974.2019.9010527
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783319987750
Anomaly detection in video aims to automatically detect the unusual occurred event and model was trained from some normal samples. Previously, reconstruction-cost-based methods were the most commonly used way to solve this problem. However, because o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a2f167995fef946ba3accc3b863c64d8
https://doi.org/10.1007/978-3-319-98776-7_59
https://doi.org/10.1007/978-3-319-98776-7_59
