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Automated building classification framework using convolutional neural network
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Adha, Augusta, Pamuncak, Arya Panji, Qiao, Wen and Laory, Irwanda (2022) Automated building classification framework using convolutional neural network. Cogent Engineering, 9 (1). doi:10.1080/23311916.2022.2065900 ISSN 2331-1916.
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Official URL: https://doi.org/10.1080/23311916.2022.2065900
Abstract
Despite extensive study, performing Rapid visual screening is still a challenging task for many countries. The challenges include the lack of trained engineers, limited resources, and a large building inventory to detect. One of the most important aspect in rapid visual screening is to establish the building classification based on the guidelines’ specific criteria. This study proposes a general framework based on Convolutional Neural Network to perform automated building classification for the rapid visual screening procedure. The method classifies buildings based on the Federal Emergency Management Agency (FEMA)-154 guidelines and uses transfer learning techniques from a pre-trained network. The Indonesian building portfolio is used as a case study and a dataset of building images generated through web-scraping on Google Search™ engines and Google StreetView™ website is used for the method validation. Results show that the proposed framework has promising potential to automate the building classification based on FEMA-154 guidelines.
| Item Type: | Journal Article | |||||||||
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| Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > T Technology (General) T Technology > TH Building construction T Technology > TJ Mechanical engineering and machinery |
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| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | |||||||||
| SWORD Depositor: | Library Publications Router | |||||||||
| Library of Congress Subject Headings (LCSH): | Buildings -- Earthquake effects , Buildings -- Earthquake effects -- Computer simulation, Buildings -- Classification -- Data processing, Automation , Human-computer interaction , Neural networks (Computer science) , Computer graphics , Buildings -- Earthquake effects -- Computer-aided design | |||||||||
| Journal or Publication Title: | Cogent Engineering | |||||||||
| Publisher: | Informa UK Limited | |||||||||
| ISSN: | 2331-1916 | |||||||||
| Official Date: | 2022 | |||||||||
| Dates: |
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| Volume: | 9 | |||||||||
| Number: | 1 | |||||||||
| DOI: | 10.1080/23311916.2022.2065900 | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Access rights to Published version: | Open Access (Creative Commons) | |||||||||
| Date of first compliant deposit: | 27 May 2022 | |||||||||
| Date of first compliant Open Access: | 30 May 2022 | |||||||||
| RIOXX Funder/Project Grant: |
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