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About Satellite Image Classification With Deep Learning
This document discusses applying convolutional neural networks (CNNs) to classify objects in high-resolution satellite imagery. CNNs have achieved great success in image classification but have seen limited success for satellite imagery due to challenges in preprocessing large satellite images for CNN input and a lack of large labeled satellite image datasets for training. The document describes a deep learning system using an ensemble of CNNs and additional neural networks to classify objects in satellite imagery into 63 classes, achieving 83% total accuracy in a competition.
Detailed Information
| Author: | ['muhammad bilal'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 7 |
| Language: | English |
| Format: | |
| Price: | FREE |
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