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Computer vision techniques for agric...
~
Bania, Rubul Kumar, (1983-)
Computer vision techniques for agricultural advancements
Record Type:
Electronic resources : Monograph/item
Title/Author:
Computer vision techniques for agricultural advancementsedited by Dibya Bora, Rubul Bania.
other author:
Bora, Dibya Jyoti,
Published:
Hershey, Pennsylvania :IGI Global,2025.
Description:
1 online resource (xxi, 548 p.) :ill.
Subject:
Artificial IntelligenceAgricultural applications.
Online resource:
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-8019-2
ISBN:
9798369380215$q(ebook)
Computer vision techniques for agricultural advancements
Computer vision techniques for agricultural advancements
[electronic resource] /edited by Dibya Bora, Rubul Bania. - Hershey, Pennsylvania :IGI Global,2025. - 1 online resource (xxi, 548 p.) :ill.
Includes bibliographic references and index.
Preface -- Chapter 1. Automating Agricultural Processes With Computer Vision: Challenges and Solutions -- Chapter 2. Unleashing Artificial Intelligence, IoT, Big Data in Food and Agricultural Industry: Strategic and Multi-Dimensional Analysis -- Chapter 3. Enhancing Food Safety and Quality Control With Computer Vision Systems -- Chapter 4. Automated Detection of Botrytis Cinerea in Grape Leaves Using Convolutional Neural Networks -- Chapter 5. Crop Health Monitoring Through AI-Based Crop Leaf Disease Detection Systems -- Chapter 6. Hybrid Deep Learning for Citrus Disease Detection: Bridging Agricultural Needs in North East India -- Chapter 7. Crayfish-Optimized CNN and Random Forest for Effective Plant Disease Detection -- Chapter 8. Prediction of Sugarcane Diseases With Self-Designed Dataset of Assam using Deep Learning Techniques -- Chapter 9. Deep Convolutional Neural Networks for Weed Detection in Polyhouse-Grown Bell Peppers: Innovations and Applications -- Chapter 10. Green Internet of Things Advancing Sustainable Technology With Smart Agriculture in India -- Chapter 11. Innovations in Autonomous Drones for Precision Agriculture: Techniques and Applications -- Chapter12. IoT and Deep Learning-Based Smart Farm Environment Optimization and Yield Prediction Platform -- Chapter 13. Machine Vision Systems for Post-Harvest Quality Assessment -- Chapter 14. Real-Time Data Processing in Agricultural Robotics --Compilation of References -- About the Contributors -- Index.
"This book aims to explore the dynamic intersection of computer vision, artificial intelligence (AI) and agriculture, offering a comprehensive overview of the latest trends, challenges, and opportunities in this rapidly evolving field"--
Mode of access: World Wide Web.
ISBN: 9798369380215$q(ebook)Subjects--Topical Terms:
995165
Artificial Intelligence
--Agricultural applications.Subjects--Index Terms:
Artificial Intelligence (AI)Index Terms--Genre/Form:
214472
Electronic books.
LC Class. No.: S494.5.D3 / C67 2025eb
Dewey Class. No.: 338.10285
Computer vision techniques for agricultural advancements
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Computer vision techniques for agricultural advancements
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edited by Dibya Bora, Rubul Bania.
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IGI Global,
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1 online resource (xxi, 548 p.) :
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ill.
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Includes bibliographic references and index.
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Preface -- Chapter 1. Automating Agricultural Processes With Computer Vision: Challenges and Solutions -- Chapter 2. Unleashing Artificial Intelligence, IoT, Big Data in Food and Agricultural Industry: Strategic and Multi-Dimensional Analysis -- Chapter 3. Enhancing Food Safety and Quality Control With Computer Vision Systems -- Chapter 4. Automated Detection of Botrytis Cinerea in Grape Leaves Using Convolutional Neural Networks -- Chapter 5. Crop Health Monitoring Through AI-Based Crop Leaf Disease Detection Systems -- Chapter 6. Hybrid Deep Learning for Citrus Disease Detection: Bridging Agricultural Needs in North East India -- Chapter 7. Crayfish-Optimized CNN and Random Forest for Effective Plant Disease Detection -- Chapter 8. Prediction of Sugarcane Diseases With Self-Designed Dataset of Assam using Deep Learning Techniques -- Chapter 9. Deep Convolutional Neural Networks for Weed Detection in Polyhouse-Grown Bell Peppers: Innovations and Applications -- Chapter 10. Green Internet of Things Advancing Sustainable Technology With Smart Agriculture in India -- Chapter 11. Innovations in Autonomous Drones for Precision Agriculture: Techniques and Applications -- Chapter12. IoT and Deep Learning-Based Smart Farm Environment Optimization and Yield Prediction Platform -- Chapter 13. Machine Vision Systems for Post-Harvest Quality Assessment -- Chapter 14. Real-Time Data Processing in Agricultural Robotics --Compilation of References -- About the Contributors -- Index.
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"This book aims to explore the dynamic intersection of computer vision, artificial intelligence (AI) and agriculture, offering a comprehensive overview of the latest trends, challenges, and opportunities in this rapidly evolving field"--
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Mode of access: World Wide Web.
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Artificial Intelligence
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Agricultural applications.
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995165
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Computer vision.
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Agricultural innovations.
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Artificial Intelligence (AI)
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Autonomous Drones.
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Big Data.
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Computer Vision.
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Crop Health Monitoring.
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Data Processing.
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Deep Learning.
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Disease Detection.
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Food Safety.
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Internet of Things (IoT)
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Neural Networks.
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Precision Agriculture.
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Quality Assessment.
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Quality Control.
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Smart Agriculture.
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Sustainable Technology.
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Yield Prediction.
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Bania, Rubul Kumar,
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1983-
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http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-8019-2
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EB S494.5.D3 C67 2025eb 2025
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http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-8019-2
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