July 2020
Intermediate to advanced
164 pages
3h 16m
English
Content preview from Deep Learning for Remote Sensing Images with Open Source Software
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In this section, we provide the essential principles of deep learning. After reading this chapter, one should have the required theoretical basis to understand what is involved in processing geospatial data in the rest of the book.
Deep learning is becoming increasingly important to solve a number of image processing tasks [1]. Among common algorithms, Convolutional Neural Network- and Recurrent Neural Network-based systems achieve state-of-the-art results on satellite and aerial imagery in many applications. For instance, synthetic aperture radar (SAR) interpretation with target recognition [2], classification of SAR time series [3], parameter inversion [4], hyperspectral image ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.