Computer Vision and Deep Learning for Remote Sensing Applications Call for Papers



* Special Issue on Computer Vision and Deep Learning for Remote Sensing Applications *

Journal: Remote Sensing (MDPI), IF 4.118

Guest Editors: Hyungtae Lee, Sungmin Eum, Claudio Piciarelli

Full info:

Deadline: accepted papers will be published continuously in the
journal (as soon as accepted) till the deadline (31 March 2021)



Today, the field of computer vision and deep learning is rapidly
progressing into many applications, including remote sensing, due to
its remarkable performance. Especially for remote sensing, a myriad of
challenges due to difficult data acquisition and annotation have not
been fully solved yet. The remote sensing community is waiting for a
breakthrough to address these challenges by utilizing high-performance
deep learning-based models that typically require large-scale
annotated datasets.

This issue is looking for such breakthroughs focusing on the advances
in remote sensing using computer vision, deep learning and artificial
intelligence. Although broad in scope, contributions with a specific
focus are expected.

For this special issue, we welcome the most recent advancements
related, but not limited to:

* Deep learning architecture for remote sensing

* Machine learning for remote sensing

* Computer vision method for remote sensing

* Classification / Detection / Regression

* Unsupervised feature learning for remote sensing

* Domain adaptation and transfer learning with computer vision and
deep learning for remote sensing

* Anomaly/novelty detection for remote sensing

* New dataset and task for remote sensing

* Remote sensing data analysis

* New remote sensing application

* Synthetic remote sensing data generation

* Real-time remote sensing

* Deep learning-based image registration

Dr. Hyungtae Lee

Dr. Sungmin Eum

Dr. Claudio Piciarelli

Guest Editors