Building type classification from street-view imagery using convolutional neural networks / by Ala’a Al-Habashna.: CS18-001/2021-3E-PDF
"Micro-level information on buildings and physical infrastructure is increasing in relevance to social, economic and environmental statistical programs. Alternative data sources and advanced analytical methods can be used to generate some of this information. This paper presents how multiple convolutional neural networks (CNNs) are finetuned to classify buildings into different types (e.g., house, apartment, industrial) using their street-view images"--Summary, page 6.
Permanent link to this Catalogue record:
publications.gc.ca/pub?id=9.905566&sl=0
| Department/Agency | Statistics Canada, issuing body. |
|---|---|
| Title | Building type classification from street-view imagery using convolutional neural networks / by Ala’a Al-Habashna. |
| Series title | Reports on special business projects |
| Publication type | Series - View Master Record |
| Language | [English] |
| Other language editions | [French] |
| Format | Electronic |
| Electronic document | |
| Note(s) | Issued also in French under title: Classification des types d'immeubles au moyen d'images prises à partir de la rue à l'aide de réseaux neuronaux convolutifs. Issued also in HTML format. "Release date: January 21, 2022." Includes bibliographical references (pages 20). |
| Publishing information | [Ottawa] : Statistics Canada = Statistique Canada, 2022. ©2022 |
| Author / Contributor | Habashna, Ala'a Al-, author. |
| Description | 1 online resource (20 pages) : charts, illustrations |
| ISBN | 9780660411682 |
| Catalogue number |
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| Departmental catalogue number | 18-001-X |
| Subject terms | Buildings -- Canada -- Classification. |
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