An Extensible and Easy-to-use Toolbox for Deep Learning Based Analysis of Remote Sensing Images

Deep Learning (DL) methods are currently the state-of-the-art in Machine Learning and Pattern Recognition. In recent years, DL has been successfully applied to Remote Sensing (RS) image processing for several tasks, from pre-processing to classification. This paper presents DeepGeo, a toolbox that p...

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Bibliographic Details
Main Authors: Maretto, Raian Vargas, Korting, Thales Sehn, Fonseca, Leila Maria Garcia
Format: Conference Proceeding
Language:English
Subjects:
Convolutional Neural Networks
Data models
Data preprocessing
Deep learning
Feature extraction
Remote sensing
Semantic Segmentation
Training
Online Access:Request full text
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Description
Summary:Deep Learning (DL) methods are currently the state-of-the-art in Machine Learning and Pattern Recognition. In recent years, DL has been successfully applied to Remote Sensing (RS) image processing for several tasks, from pre-processing to classification. This paper presents DeepGeo, a toolbox that provides state-of-the-art DL algorithms for RS image classification and analysis. DeepGeo focuses on providing easy-to-use and extensible methods, making it easier to those RS analysts without strong programming skills. It is distributed as free and open source package and is available at https: //github.com/rvmaretto/deepgeo.
ISSN:2153-7003
DOI:10.1109/IGARSS.2019.8898823