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Seasonal_Domain_Shift_in_the_Global_South_Dataset_and_Deep_Features_Analysis.pdf (1.14 MB)
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Seasonal domain shift in the global south: dataset and deep features analysis

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Domain 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

2160-7516

Publisher

IEEE

Event name

Computer Vision and Pattern Recognition (CVPR) EarthVision

Event location

Vancouver, Canada

Event type

conference

Event date

18 June 2023

ISBN

9798350302509

Department 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

2023-04-12

First Open Access (FOA) Date

2023-04-14

First Compliant Deposit (FCD) Date

2023-04-14

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