Recognition of urban structures in multiband data by means of ART networks
International Geoscience and Remote Sensing Symposium (IGARSS), Vol: 1, Page: 400-402
1998
- 2Citations
- 4Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Conference Paper Description
In this paper multiband images of a urban environment are analyzed and interpreted by means of a neural network approach. In particular, the advantages found by using Adaptive Resonance Theory networks both for a spatial and spectral analysis of the data are shown and commented. Moreover, we simplify existing similar approaches by introducing a clustering step that automatically solves the problem of class redundancy, typical of the ART classification output. Results are given for a photo+SAR image of Santa Monica, Los Angeles.
Bibliographic Details
Institute of Electrical and Electronics Engineers (IEEE)
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