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Computer vision techniques for agric...

Bora, Dibya Jyoti, (1986-)

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Computer vision techniques for agricultural advancements

Record Type:	Electronic resources : Monograph/item
Title/Author:	Computer vision techniques for agricultural advancements/ edited by Dibya Bora, Rubul Bania.
other author:	Bora, Dibya Jyoti,
Published:	Hershey, Pennsylvania :IGI Global, : 2025.,
Description:	1 online resource (xxi, 548 p.) :ill.
[NT 15003449]:	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.
Subject:	Artificial Intelligence - Agricultural applications. -
Online resource:	https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-8019-2
ISBN:	9798369380215

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: 9798369380215Subjects--Topical Terms:

3793472
Artificial Intelligence
--Agricultural applications.Subjects--Index Terms:

Artificial Intelligence (AI)Index Terms--Genre/Form:

542853
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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245 0 0 $a Computer vision techniques for agricultural advancements $h [electronic resource] / $c edited by Dibya Bora, Rubul Bania.
260 $a Hershey, Pennsylvania : $b IGI Global, $c 2025.
300 $a 1 online resource (xxi, 548 p.) : $b ill.
504 $a Includes bibliographic references and index.
505 0 $a 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.
520 3 $a "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"-- $c Provided by publisher.
538 $a Mode of access: World Wide Web.
650 0 $a Artificial Intelligence $x Agricultural applications. $3 3793472
650 0 $a Computer vision. $3 540671
650 0 $a Agricultural innovations. $3 570532
653 $a Artificial Intelligence (AI)
653 $a Autonomous Drones.
653 $a Big Data.
653 $a Computer Vision.
653 $a Crop Health Monitoring.
653 $a Data Processing.
653 $a Deep Learning.
653 $a Disease Detection.
653 $a Food Safety.
653 $a Internet of Things (IoT)
653 $a Neural Networks.
653 $a Precision Agriculture.
653 $a Quality Assessment.
653 $a Quality Control.
653 $a Smart Agriculture.
653 $a Sustainable Technology.
653 $a Yield Prediction.
655 4 $a Electronic books. $2 lcsh $3 542853
700 1 $a Bora, Dibya Jyoti, $d 1986- $3 3793470
700 1 $a Bania, Rubul Kumar, $d 1983- $3 3793471
710 2 $a IGI Global. $3 1361470
776 0 $c (Original) $w (DLC)2024054420
776 0 8 $i Print version: $z 9798369380192 $w (DLC) 2024054420
856 4 0 $u https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-8019-2