Deep learning for remote sensing images with open source software / (Record no. 130648)

000 -LEADER
fixed length control field 03450cam a2200601 i 4500
001 - CONTROL NUMBER
control field 9781003020851
003 - CONTROL NUMBER IDENTIFIER
control field FlBoTFG
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220509193133.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS--GENERAL INFORMATION
fixed length control field m d | |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr |||||||||||
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 200524s2020 flua ob 001 0 eng
040 ## - CATALOGING SOURCE
Original cataloging agency OCoLC-P
Language of cataloging eng
Description conventions rda
Transcribing agency OCoLC-P
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781000093599
-- electronic book
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 100009359X
-- electronic book
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781003020851
-- electronic book
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1003020852
-- electronic book
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Cancelled/invalid ISBN 9780367858483
-- hardcover
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781000093612
-- (ePub ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1000093611
-- (ePub ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781000093605
-- (Mobipocket ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1000093603
-- (Mobipocket ebook)
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1201/9781003020851
Source of number or code doi
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)1158508782
Canceled/invalid control number (OCoLC)1173644635
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC-P)1158508782
050 04 - LIBRARY OF CONGRESS CALL NUMBER
Classification number G70.4
Item number .C75 2020
072 #7 - SUBJECT CATEGORY CODE
Subject category code TEC
Subject category code subdivision 036000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code TEC
Subject category code subdivision 015000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM
Subject category code subdivision 012050
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code RGW
Source bicssc
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 621.36/78
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Cresson, Rémi,
Relator term author.
245 10 - TITLE STATEMENT
Title Deep learning for remote sensing images with open source software /
Statement of responsibility, etc Rémi Cresson.
250 ## - EDITION STATEMENT
Edition statement First edition.
264 #1 -
-- Boca Raton, FL :
-- CRC Press, Taylor & Francis Group,
-- [2020]
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource (xi, 151 pages) :
Other physical details color illustrations.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
490 0# - SERIES STATEMENT
Series statement Signal and image processing of Earth observation series
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 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.
520 ## - SUMMARY, ETC.
Summary, etc "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"--
-- Provided by publisher.
588 ## -
-- OCLC-licensed vendor bibliographic record.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Remote sensing
General subdivision Data processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Remote-sensing images.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Image processing
General subdivision Digital techniques.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Neural networks (Computer science)
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Open source software.
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element TECHNOLOGY / Remote Sensing
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element TECHNOLOGY / Imaging Systems
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element COMPUTERS / Computer Graphics / Image Processing (see also PHOTOGRAPHY / Techniques / Digital)
Source of heading or term bisacsh
856 40 - ELECTRONIC LOCATION AND ACCESS
Materials specified Taylor & Francis
Uniform Resource Identifier https://www.taylorfrancis.com/books/9781003020851
856 42 - ELECTRONIC LOCATION AND ACCESS
Materials specified OCLC metadata license agreement
Uniform Resource Identifier http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf

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