Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Hajar Zoubir"'
Autor:
Hajar Zoubir, Mustapha Rguig, Mohamed El Aroussi, Abdellah Chehri, Rachid Saadane, Gwanggil Jeon
Publikováno v:
Remote Sensing, Vol 14, Iss 19, p 4882 (2022)
Conventional practices of bridge visual inspection present several limitations, including a tedious process of analyzing images manually to identify potential damages. Vision-based techniques, particularly Deep Convolutional Neural Networks, have bee
Externí odkaz:
https://doaj.org/article/1e0cabb818d5494e9a1ab9d80230a589
Publikováno v:
Innovations in Smart Cities Applications Volume 6 ISBN: 9783031268519
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bafce8cea9e205b214ff77b018cababc
https://doi.org/10.1007/978-3-031-26852-6_56
https://doi.org/10.1007/978-3-031-26852-6_56
Publikováno v:
Electronics. 11:3357
Bridges deteriorate over time, which requires the continuous monitoring of their condition. There are many digital technologies for inspecting and monitoring bridges in real-time. In this context, computer vision has extensively studied cracks to aut
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f9c0620117f1b3ebd70da87cf0f7c8c
https://doi.org/10.3390/electronics11203357
https://doi.org/10.3390/electronics11203357
Publikováno v:
MATEC Web of Conferences, Vol 349, p 03014 (2021)
Using Unmanned Aerial Systems (UASs) for bridge visual inspection automation necessitates the implementation of Deep Convolutional Neural Networks (DCNNs) to process efficiently the large amount of data collected by the UASs sensors. However, these n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::271646a6a6b2db644d5fc72940135899
https://www.matec-conferences.org/articles/matecconf/pdf/2021/18/matecconf_iceaf2021_03014.pdf
https://www.matec-conferences.org/articles/matecconf/pdf/2021/18/matecconf_iceaf2021_03014.pdf