Remote Sensing: Learning and Computing

A GRSL special stream – 2017
· Prof. Qi Wang, GRSL Associate Editor, Northwestern Polytechnical University, China
· Prof. Turgay Celik, Guest Editor, University of the Witwatersrand, South Africa
· Prof. Ji Liu, Guest Editor, University of Rochester, USA
· Prof. Bo Liu, Guest Editor, Auburn University, USA

With the development of earth observation techniques, a tremendous number of remote sensing images are acquired every year. This is for one thing beneficial to the research community because more information is available and helpful, but on the other hand means much challenging for the automatic analysis and computation. To tackle this problem, learning based algorithms are thought to be promising and effective, especially for the state-of-the-art machine learning techniques and statistical computing methods, such as deep learning, graphical models, sparse coding and kernel machines.

The IEEE Geoscience and Remote Sensing Letters (IEEE GRSL) calls for papers for a Special Stream on “Remote Sensing: Learning and Computing”. The papers will be based on the latest research results and outcomes about learning and computing for remote sensing images. Particularly, original submissions reporting recent advances in the machine learning approaches towards analyzing and understanding of remote sensing images are encouraged.

Starting date for submission: 1 February 2017
Closing date for submission: 15 July 2017
Paper Submission Link:

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