Deep learning for remote sensing images with open source software

Deep learning for remote sensing images with open source software

"In today's world, deep learning source codes and a plethora of open access geospatial images are available, but readers are missing the educational tools. This is the first practical book to introduce deep learning techniques using free open source tools for processing real world remote s...

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Detalles Bibliográficos
Otros Autores: Cresson, Rémi, author (author)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Boca Raton, Florida ; London ; New York : CRC Press [2020]
Edición:First edition
Colección:Signal and image processing of Earth observations series.
Materias:
Remote sensing > Data processing.
Remote-sensing images.
Image processing > Digital techniques.
Machine learning.
Neural networks (Computer science)
Open source software.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009714837906719
Tabla de Contenidos:
  • Deep learning backgrounds
  • Software
  • Data used : the Tokyo dataset
  • A simple convolutional neural network
  • Fully convolutional neural network
  • Classifiers on deep features
  • Dealing with multiple sources
  • Semantic segmentation of optical imagery
  • Data used : the Amsterdam dataset
  • Mapping buildings
  • Gap filling of optical images : principle
  • The Marmande dataset
  • Pre-processing
  • Model training
  • Inference.

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