Abstract | ||
---|---|---|
This letter proposes a change detection algorithm for damage assessment caused by fires in Ireland using Sentinel 1 data. The novelty, in this letter, is a feature extraction within tunable Q discrete wavelet transform (TQWT) using higher order log cumulants of fractional Fourier transform (FrFT), which were fed into a stacked autoencoder (SAE) to distinguish changed and unchanged areas. The extra... |
Year | DOI | Venue |
---|---|---|
2018 | 10.1109/LGRS.2017.2786344 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Feature extraction,Synthetic aperture radar,Decoding,Discrete wavelet transforms,Support vector machines | Computer vision,Autoencoder,Pattern recognition,Synthetic aperture radar,Support vector machine,Feature extraction,Artificial intelligence,Discrete wavelet transform,Classifier (linguistics),Fractional Fourier transform,Mathematics,Wavelet transform | Journal |
Volume | Issue | ISSN |
15 | 2 | 1545-598X |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
2 |
Name | Order | Citations | PageRank |
---|---|---|---|
P. Planinšič | 1 | 27 | 7.70 |
Dusan Gleich | 2 | 24 | 6.92 |