Deep Learning for Agricultural Visual Perception (Record no. 184929)

MARC details
000 -LEADER
fixed length control field 03481nam a22006255i 4500
001 - CONTROL NUMBER
control field 978-981-99-4973-1
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423130105.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 230920s2023 si | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789819949731
-- 978-981-99-4973-1
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-981-99-4973-1
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q334-342
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA347.A78
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM004000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Wang, Rujing.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
245 10 - TITLE STATEMENT
Title Deep Learning for Agricultural Visual Perception
Medium [electronic resource] :
Remainder of title Crop Pest and Disease Detection /
Statement of responsibility, etc by Rujing Wang, Lin Jiao, Kang Liu.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2023.
264 #1 -
-- Singapore :
-- Springer Nature Singapore :
-- Imprint: Springer,
-- 2023.
300 ## - PHYSICAL DESCRIPTION
Extent XII, 131 p. 1 illus.
Other physical details online resource.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
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-- rdamedia
338 ## -
-- online resource
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-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Chapter 1. Introduction -- Chapter 2. Deep Learning Technology -- Chapter 3. Large-Scale Agricultural Pest and Disease Datasets -- Chapter 4. Sampling-balanced Region Proposal Network for Pest Detection -- Chapter 5. Crop Pest Detection Methods in Field -- Chapter 6. A CNN-based Arbitrary-oriented Wheat Disease Detection Method.
520 ## - SUMMARY, ETC.
Summary, etc This monograph provides a detailed and systematic introduction to the application of deep learning technology in the intelligent monitoring of crop diseases and pests. Taking 24 types of crop pests, wheat aphids, and wheat diseases with complex backgrounds as examples, a large-scale crop pest and disease dataset was constructed to provide necessary data support for the deep learning module. Various schemes for identifying and detecting large-scale crop diseases and pests based on deep convolutional neural network technology have also been proposed. This book can be used as a reference for teachers and students majoring in agriculture, computer science, artificial intelligence, intelligent science and technology, and other related fields in higher education institutions. It can also be used as a reference book for researchers in fields such as image processing technology, intelligent manufacturing, and high-tech applications.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence.
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 Computer vision.
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 Image processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Agriculture.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer Imaging, Vision, Pattern Recognition and Graphics.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer Vision.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine Learning.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Image Processing.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Agriculture.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Jiao, Lin.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Liu, Kang.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9789819949724
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9789819949748
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9789819949755
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-981-99-4973-1">https://doi.org/10.1007/978-981-99-4973-1</a>
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks-CSE-Springer

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