Current Limits and New Challenges and Opportunities in Soft Computing, Machine Learning and Computational Intelligence for Remote Sensing

Dear Colleagues,

Remote sensing (RS) has been an inexhaustible source of data in which the most innovative techniques from the world of computational intelligence have been applied. The different studies carried out in recent years show great synergies between both disciplines. Despite the good results, however, the limitations of computational techniques in the context of RS should be delimited to make new proposals that could increase the quality of the RS products.

All the above is more important, if possible, bearing in mind that remote sensors are being used in areas that would originally be outside the traditional scope of RS, such as autonomous vehicles or real-time monitoring for security. These new opportunities involve the need to develop novel methodologies that adapt the general RS framework (including management of data with high variety, velocity, and volume).

This Special Issue thus focuses on the exploration of novel ideas regarding disciplines related to computational intelligence in RS. We call for contributions that describe novel methods and ongoing research, including algorithm development, training strategies, and implementations, but also studies to find out the real limitations of current computational techniques in RS. We specifically invite you to submit the most recent advances in the following (or related) topics:

• Change and target detection in single- and multitemporal analysis;
• Deep, transfer, and active learning from single and multiple data sources;
• Large-scale RS data analysis;
• Machine learning and pattern recognition methodologies for RS;
• Multimodal data fusion;
• Near-real time and real-time processing;
• Semantic and image segmentation.

Prof. Dr. Jorge Garcia-Gutierrez
Dr. Maria del Mar Martinez-Ballesteros
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

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