K-textures, a self-supervised hard clustering deep learning algorithm for satellite image segmentation

K-textures, a self-supervised hard clustering deep learning algorithm for satellite image segmentation

Deep learning self-supervised algorithms that can segment an image in a fixed number of hard clusters such as the k-means algorithm and with an end-to-end deep learning approach are still lacking. Here, we introduce the k-textures algorithm which provides self-supervised segmentation of a 4-band ima...

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Bibliographic Details
Main Authors: Fabien H. Wagner, Ricardo Dalagnol, Alber H. Sánchez, Mayumi C. M. Hirye, Samuel Favrichon, Jake H. Lee, Steffen Mauceri, Yan Yang, Sassan Saatchi
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-09-01
Series:Frontiers in Environmental Science
Subjects:
deep learning - artificial neural network
segmentation (image processing)
tropical forest
landcover
tensorflow (2)
self-supervised segmentation
Online Access:https://www.frontiersin.org/articles/10.3389/fenvs.2022.946729/full

Internet

https://www.frontiersin.org/articles/10.3389/fenvs.2022.946729/full

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