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About An Introduction To Deep Learning On Remote Sensing Images (Tutorial) - Mdl4eo
This document provides an introduction to using deep learning and neural networks to classify remote sensing images. It describes a tutorial where a convolutional neural network (CNN) will be trained on patches extracted from a Sentinel-2 image to classify each pixel as one of six classes. The steps include: 1) Normalizing the image bands, 2) Extracting patches from the image and associated labels to create a training dataset, 3) Training a small CNN model on the patches to classify each one, and 4) Applying the trained model to the full image to generate a classified land cover map. Open source tools from Orfeo Toolbox and TensorFlow will be used for the deep learning and image processing tasks.
Detailed Information
| Author: | ['shivachandra'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 13 |
| Language: | English |
| Format: | |
| Price: | FREE |
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