Seasonal_Domain_Shift_in_the_Global_South_Dataset_and_Deep_Features_Analysis.pdf (1.14 MB)
Seasonal domain shift in the global south: dataset and deep features analysis
conference contribution
posted on 2023-06-19, 08:35 authored by Georgios Voulgaris, Andy PhilippidesAndy Philippides, Jonathan DolleyJonathan Dolley, Jeremy ReffinJeremy Reffin, Fiona MarshallFiona Marshall, Novi QuadriantoNovi QuadriantoDomain shifts during seasonal variations are an important aspect affecting the robustness of aerial scene classification and so it is crucial that such variation is captured within aerial scene datasets. This is more evident in geographic locations in the global South, where aerial coverage is scarcer and the rural and semi-urban landscape varies dramatically between wet and dry seasons. As current datasets do not offer the ability to experiment with domain shifts due to seasonal variations, this work proposes a labelled dataset for classifying land use from aerial images, comprising both wet and dry season data from Ghaziabad in India. Moreover, we conduct a thorough investigation into how image features, namely colour, shape, and texture, influence the accuracy of scene classification. We demonstrate that a combination of an architecture that extracts salient features, with the implementation of a larger receptive field improves classification performance when applied to both shallow or deep architectures by extracting invariant feature representations across domains.
History
Publication status
- Published
File Version
- Accepted version
Journal
Conference on Computer Vision and Pattern Recognition (CVPR)ISSN
2160-7516Publisher
IEEEPublisher URL
External DOI
Event name
Computer Vision and Pattern Recognition (CVPR) EarthVisionEvent location
Vancouver, CanadaEvent type
conferenceEvent date
18 June 2023ISBN
9798350302509Department affiliated with
- Informatics Publications
Research groups affiliated with
- Sussex Sustainability Research Programme Publications
Notes
© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2023-04-12First Open Access (FOA) Date
2023-04-14First Compliant Deposit (FCD) Date
2023-04-14Usage metrics
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