Deep Learning for Remote Sensing Images with Open Source Software - Info and Reading Options
By Rémi Cresson
"Deep Learning for Remote Sensing Images with Open Source Software" was published by Taylor & Francis Group in 2022 - Boca Raton London New York, it has 151 pages and the language of the book is English.
“Deep Learning for Remote Sensing Images with Open Source Software” Metadata:
- Title: ➤ Deep Learning for Remote Sensing Images with Open Source Software
- Author: Rémi Cresson
- Language: English
- Number of Pages: 151
- Publisher: Taylor & Francis Group
- Publish Date: 2022
- Publish Location: Boca Raton London New York
“Deep Learning for Remote Sensing Images with Open Source Software” Subjects and Themes:
- Subjects: ➤ Remote sensing - Data processing - Remote-sensing images - Image processing - Digital techniques - Machine learning - Neural networks (Computer science) - Open source software - Télédétection - Informatique - Images-satellite - Traitement d'images - Techniques numériques - Apprentissage automatique - Réseaux neuronaux (Informatique) - Logiciels libres - Digital imaging - TECHNOLOGY / Remote Sensing - TECHNOLOGY / Imaging Systems - COMPUTERS / Computer Graphics / Image Processing (see also PHOTOGRAPHY / Techniques / Digital)
Edition Specifications:
- Pagination: 152
Edition Identifiers:
- The Open Library ID: OL36771779M - OL25247992W
- ISBN-13: 9780367518981 - 9780367858483
- All ISBNs: 9780367518981 - 9780367858483
AI-generated Review of “Deep Learning for Remote Sensing Images with Open Source Software”:
"Deep Learning for Remote Sensing Images with Open Source Software" Description:
Open Data:
"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 sensing images. The approaches are generic and adapted to suit many applications for various remote sensing images processing in landcover mapping, forestry, urban, in disaster mapping, image restoration, etc. Written with practitioners and students in mind, this book helps readers link together the theory and practical use of existing tools and data to create their own remote sensing data processing"--
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