Ensemble Learning Approaches Based on Covariance Pooling of CNN Features for High Resolution Remote Sensing Scene Classification

Ensemble Learning Approaches Based on Covariance Pooling of CNN Features for High Resolution Remote Sensing Scene Classification

Remote sensing image scene classification, which consists of labeling remote sensing images with a set of categories based on their content, has received remarkable attention for many applications such as land use mapping. Standard approaches are based on the multi-layer representation of first-orde...

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Autori principali: Sara Akodad, Lionel Bombrun, Junshi Xia, Yannick Berthoumieu, Christian Germain
Natura: Articolo
Lingua:English
Pubblicazione: MDPI AG 2020-10-01
Serie:Remote Sensing
Soggetti:
transfer learning
covariance matrices
log-euclidean metric
ensemble learning
remote sensing scene classification
fisher vector
Accesso online:https://www.mdpi.com/2072-4292/12/20/3292

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https://www.mdpi.com/2072-4292/12/20/3292

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