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
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| Title | Building type classification from street-view imagery using convolutional neural networks / by Ala’a Al-Habashna. |
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| Publication type | Monograph - View Master Record |
| Language | [English] |
| Other language editions | [French] |
| Format | Digital text |
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| Description | 1 online resource (20 pages) : charts, illustrations |
| ISBN | 9780660411682 |
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| Departmental catalogue number | 18-001-X |
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