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Cited by 2,969

The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

Bag-of-visual-words and spatial extensions for land-use classification

Yang, Yi, Newsam, Shawn·2010·Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems

Abstract

We investigate bag-of-visual-words (BOVW) approaches to land-use classification in high-resolution overhead imagery. We consider a standard non-spatial representation in which the frequencies but not the locations of quantized image features are used to discriminate between classes analogous to how words are used for text document classification without regard to their order of occurrence. We also consider two spatial extensions, the established spatial pyramid match kernel which considers the absolute spatial arrangement of the image features, as well as a novel method which we term the spatial co-occurrence kernel that considers the relative arrangement. These extensions are motivated by the importance of spatial structure in geographic data.

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Research works printed but not linked: 13

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  10. 10.1364/AO.43.000210 · DOI
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  13. 10.2307/143141 · DOI · Paper page

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Metadata

Authors
Yang, Y., & Newsam, S.
Venue
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Publisher
ACM
Published
2010-11-02
Pages
270-279
OpenAlex
W1980038761
Cited by
2,969
References
12
FWCI
15.85
Type
conference paper
Language
en
Open access
closed
Funders
Division of Information and Intelligent Systems (IIS-0917069)

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Yang, Y., & Newsam, S. (2010). Bag-of-visual-words and spatial extensions for land-use classification. Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems. https://doi.org/10.1145/1869790.1869829

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