{"product_id":"deep-learning-for-remote-sensing-images-with-open-source-software-paperback","title":"Deep Learning for Remote Sensing Images with Open Source Software - Paperback","description":"\u003cp\u003eby \u003cb\u003eRémi Cresson\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eIn today's world, deep learning source codes and a plethora of open access geospatial images are readily available and easily accessible. However, most people are missing the educational tools to make use of this resource. \u003cb\u003e\u003ci\u003eDeep Learning for Remote Sensing Images with Open Source Software\u003c\/i\u003e\u003c\/b\u003e is the first practical book to introduce deep learning techniques using free open source tools for processing real world remote sensing images. The approaches detailed in this book are generic and can be adapted to suit many different applications for remote sensing image processing, including landcover mapping, forestry, urban studies, disaster mapping, image restoration, etc. Written with practitioners and students in mind, this book helps link together the theory and practical use of existing tools and data to apply deep learning techniques on remote sensing images and data. \u003c\/p\u003e\u003cp\u003eSpecific Features of this Book: \u003c\/p\u003e\u003cul\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eThe first book that explains how to apply deep learning techniques to public, free available data (Spot-7 and Sentinel-2 images, OpenStreetMap vector data), using open source software (QGIS, Orfeo ToolBox, TensorFlow)\u003c\/li\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003ePresents approaches suited for real world images and data targeting large scale processing and GIS applications\u003c\/li\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eIntroduces state of the art deep learning architecture families that can be applied to remote sensing world, mainly for landcover mapping, but also for generic approaches (e.g. image restoration)\u003c\/li\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eSuited for deep learning beginners and readers with some GIS knowledge. No coding knowledge is required to learn practical skills.\u003c\/li\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eIncludes deep learning techniques through many step by step remote sensing data processing exercises.\u003c\/li\u003e \u003c\/ul\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003eRemi Cresson received the M. Sc. in electrical engineering from the Grenoble Institute of Technology, France, 2009. He is with the Land, Environment, Remote Sensing and Spatial Information Joint Research Unit (UMR TETIS), at the French Research Institute of Science and Technology for Environment and Agriculture (Irstea), Montpellier, France. His research and engineering interests include remote sensing image processing, High Performance Computing, and geospatial data inter-operability. He is member of the Orfeo ToolBox Project Steering Committee and charter member of the Open source geospatial foundation (OSGEO).\u003c\/p\u003e\u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 152\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.35 x 9.21 x 6.14 IN\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e January 16, 2022\u003c\/div\u003e","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":42099597246599,"sku":"9780367518981","price":80.98,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0601\/2623\/2711\/files\/9463208c9736b63182eaa3c554d02724.webp?v=1732375880","url":"https:\/\/booksby.splitshops.com\/products\/deep-learning-for-remote-sensing-images-with-open-source-software-paperback","provider":"Books by splitShops","version":"1.0","type":"link"}