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NITK Summer School on Machine learning and Deep Learning to Remote sensing Applications


Machine and deep learning tackle the challenges in handling big data. These tools offer many potential applications in the field of remote sensing data processing and analysis. One such potential task is in effective and efficient classification of remotely sensed imagery. The strengths of machine and deep learning methods include the capacity to handle data of high dimensionality and to map classes with very complex characteristics.

However, implementing a machine and deep learning classification method is not straightforward, and the literature provides conflicting advice regarding many key issues. Jointly organised by IEEE Geoscience and Remote Sensing Society, Bangalore Section, NITK IEEE Student Branch, and the Department of Electronics and Communication Engineering, NIT Karnataka, Surathkal, India from July 5 -16, 2021, the summer school presented tutorials for application of machine and deep learning for remote sensing data.

There were lectures on many real applications of remote sensing. The two weeks online summer school provided an intensive understanding of how to use the machine and deep learning algorithms and introduction of the software tools for solving the practical problems in the remote sensing domain


Last Updated: 22-11-2021 09:43 AM Updated By: Admin

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