A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
A Curation of Image Datasets for Urban Segmentation Applications
https://orcid.org/http://orcid.org/0000-0001-6360-5013
https://orcid.org/http://orcid.org/0009-0001-8026-1344
https://orcid.org/http://orcid.org/0009-0005-7102-0046
https://orcid.org/http://orcid.org/0000-0003-2425-9685
https://orcid.org/http://orcid.org/0000-0001-5757-736X
The uprising share and effect of artificial intelligence in nearly all research fields are considerable, and it has recently arisen in the field of civil engineering as well. For pre-and post-disaster scenarios, the use of segmentation is now required to extract individual components of infrastructure. With the recent advancements in technology and deep learning methods, obtaining more reliable segmentation results is possible. Unfortunately, the readily available datasets that can be used for training and testing deep learning architectures are not easily traceable. Therefore, in order to find the related datasets, each researcher needs to perform an extended search to find these datasets and investigate the access options. This paper presents detailed information on content, coverage, type, and access steps for carefully curated datasets. The information in this paper will be an efficient starting point for the researchers aiming to perform segmentation tasks for civil engineering applications.
A Curation of Image Datasets for Urban Segmentation Applications
https://orcid.org/http://orcid.org/0000-0001-6360-5013
https://orcid.org/http://orcid.org/0009-0001-8026-1344
https://orcid.org/http://orcid.org/0009-0005-7102-0046
https://orcid.org/http://orcid.org/0000-0003-2425-9685
https://orcid.org/http://orcid.org/0000-0001-5757-736X
The uprising share and effect of artificial intelligence in nearly all research fields are considerable, and it has recently arisen in the field of civil engineering as well. For pre-and post-disaster scenarios, the use of segmentation is now required to extract individual components of infrastructure. With the recent advancements in technology and deep learning methods, obtaining more reliable segmentation results is possible. Unfortunately, the readily available datasets that can be used for training and testing deep learning architectures are not easily traceable. Therefore, in order to find the related datasets, each researcher needs to perform an extended search to find these datasets and investigate the access options. This paper presents detailed information on content, coverage, type, and access steps for carefully curated datasets. The information in this paper will be an efficient starting point for the researchers aiming to perform segmentation tasks for civil engineering applications.
A Curation of Image Datasets for Urban Segmentation Applications
https://orcid.org/http://orcid.org/0000-0001-6360-5013
https://orcid.org/http://orcid.org/0009-0001-8026-1344
https://orcid.org/http://orcid.org/0009-0005-7102-0046
https://orcid.org/http://orcid.org/0000-0003-2425-9685
https://orcid.org/http://orcid.org/0000-0001-5757-736X
The uprising share and effect of artificial intelligence in nearly all research fields are considerable, and it has recently arisen in the field of civil engineering as well. For pre-and post-disaster scenarios, the use of segmentation is now required to extract individual components of infrastructure. With the recent advancements in technology and deep learning methods, obtaining more reliable segmentation results is possible. Unfortunately, the readily available datasets that can be used for training and testing deep learning architectures are not easily traceable. Therefore, in order to find the related datasets, each researcher needs to perform an extended search to find these datasets and investigate the access options. This paper presents detailed information on content, coverage, type, and access steps for carefully curated datasets. The information in this paper will be an efficient starting point for the researchers aiming to perform segmentation tasks for civil engineering applications.
A Curation of Image Datasets for Urban Segmentation Applications
Lecture Notes in Civil Engineering
Erberik, Murat Altug (editor) / Askan, Aysegul (editor) / Kockar, Mustafa Kerem (editor) / Bayraktar, M. (author) / Bacik, Y. E. (author) / Sert, O. (author) / Aldemir, A. (author) / Güldür Erkal, B. (author)
International Conference on Energy and Environmental Science ; 2023 ; Antalya, Türkiye
Proceedings of the 7th International Conference on Earthquake Engineering and Seismology ; Chapter: 43 ; 509-521
2024-06-13
13 pages
Article/Chapter (Book)
Electronic Resource
English
| British Library Online Contents | 2018
| British Library Online Contents | 2018
| Taylor & Francis Verlag | 2018
| Taylor & Francis Verlag | 2009
| British Library Online Contents | 2009