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008211202t20222022oncda   ob   f000 0 eng d
020 |a9780660411682
040 |aCaOODSP|beng|erda|cCaOODSP
043 |an-cn---
0861 |aCS18-001/2021-3E-PDF
1001 |aHabashna, Ala'a Al-, |eauthor.
24510|aBuilding type classification from street-view imagery using convolutional neural networks / |cby Ala’a Al-Habashna.
264 1|a[Ottawa] : |bStatistics Canada = Statistique Canada, |c2022.
264 4|c©2022
300 |a1 online resource (20 pages) : |bcharts, illustrations
336 |atext|btxt|2rdacontent
337 |acomputer|bc|2rdamedia
338 |aonline resource|bcr|2rdacarrier
4901 |aReports on special business projects
500 |aIssued 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.
500 |aIssued also in HTML format.
500 |a"Release date: January 21, 2022."
504 |aIncludes bibliographical references (pages 20).
520 |a"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.
650 0|aBuildings|zCanada|xClassification.
7102 |aStatistics Canada, |eissuing body.
77508|tClassification des types d'immeubles au moyen d'images prises à partir de la rue à l'aide de réseaux neuronaux convolutifs / |w(CaOODSP)9.905567
830#0|aReports on special business projects.|w(CaOODSP)9.826502
85640|qPDF|s1.73 MB|uhttps://publications.gc.ca/collections/collection_2022/statcan/18-001-x/18-001-x2021003-eng.pdf
8564 |qHTML|sN/A|uhttps://www150.statcan.gc.ca/n1/pub/18-001-x/18-001-x2021003-eng.htm