Abstract
Building age is a key factor for building energy efficiency, valuation of real estate objects and urban planning, while previous research has been limited by the available building age data and efficient ways to estimate building age information. This paper presents an automated workflow for estimating building age from street view images. A building age dataset consisting of street view images that are labeled with the date of construction is created for Amsterdam. We designed a deep convolutional neural network for the estimation of building age and achieved a total accuracy of 81%. This research utilizes publicly available data, street view images, and construction dates of buildings, to perform the estimation of building age with an automated manner.
| Original language | English |
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| Title of host publication | Proceedings of 2021 7th IEEE International Conference on Network Intelligence and Digital Content, IC-NIDC 2021 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 102-106 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781665405829 |
| DOIs | |
| Publication status | Published - 2021 |
| Externally published | Yes |
| Event | 7th IEEE International Conference on Network Intelligence and Digital Content, IC-NIDC 2021 - Beijing, China Duration: 17 Nov 2021 → 19 Nov 2021 |
Publication series
| Name | Proceedings of 2021 7th IEEE International Conference on Network Intelligence and Digital Content, IC-NIDC 2021 |
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Conference
| Conference | 7th IEEE International Conference on Network Intelligence and Digital Content, IC-NIDC 2021 |
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| Country/Territory | China |
| City | Beijing |
| Period | 17/11/21 → 19/11/21 |
Bibliographical note
Publisher Copyright:© 2021 IEEE.
Keywords
- Building Age
- Street View Imagery
- Urban Environment
