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Computational Intelligence and Image Processing in Agriculture
Applications and Innovations

Jay Kumar Pandey (Edited by), Mritunjay Rai (Edited by), Tanmay Sarkar (Edited by)

9781394320875, Wiley

Hardback, published 12 January 2026

272 pages
28 x 19 x 2.4 cm, 1.07 kg

Revolutionizing Agricultural Quality Control with AI, Image Processing, and Computational Intelligence Techniques

As the global demand for high-quality, sustainable agricultural products increases, advanced technology becomes critical in meeting these challenges. Computational Intelligence and Image Processing in Agriculture explores how innovative technologies are transforming agricultural quality evaluation. Combining foundational concepts with practical applications, this comprehensive text delves into innovative techniques to improve accuracy, efficiency, and sustainability in quality control.

Addressing key challenges faced by researchers, practitioners, and industry professionals, contributions from leading experts in AI, agriculture, and computational intelligence provide a deep understanding of technologies such as deep learning, computer vision, and AI-driven robotics. Real-world examples, step-by-step tutorials, and code snippets make the concepts accessible and actionable, while coverage of emerging trends and future directions highlights the evolving landscape of agricultural technology. Offering interdisciplinary insights and practical tools to modernize evaluation techniques, reduce waste, enhance food safety, and meet the growing demands of sustainable farming practices, this book:

  • Addresses challenges and solutions for real-time monitoring systems in agriculture
  • Highlights cutting-edge applications such as AI-driven robotics and LiDAR in farming
  • Emphasizes sustainability and environmental impact through technological innovation
  • Offers detailed coverage of image analysis algorithms for quality control
  • Discusses ethical and environmental implications of technology in agriculture

This book is ideal for advanced undergraduate and graduate courses in agricultural engineering, computer science, and AI applications. It is also an essential reference for professionals including agricultural scientists, AI practitioners, and quality control experts.

Preface vii

Acknowledgments ix

1 Grain Quality Assessment: Image-based Techniques for Grain Analysis, Detecting Contaminants and Impurities and Real-world Applications 1

2 AI-driven Robotics in Agriculture 15

3 Computer Vision in Agriculture: Object Detection, Recognition, and Image Segmentation Techniques and Advanced Image Analysis 31

4 Artificial Intelligence and Machine Learning in Agriculture: Novel Techniques, Implementation Strategies, and Application 55

5 A Novel Approach Toward Computational Image Processing and Strategies for Precision Agriculture 73

6 Adoption of Advanced Technologies in Soilless Modern Agriculture 97

7 Computer Vision in Agriculture 113

8 Quality Evaluation of Fruits and Vegetables 125

9 Ensuring Quality in Fruits and Vegetables: Strategies and Tools 143

10 Mapping and Validation of Fusion-based Classification of Land Use and Land Cover Using Remote Sensing Satellite Images 155

11 Computer Vision Applications for Sustainable Agriculture 165

12 Autonomous Drones and AI Applications in Agriculture for Monitoring and Pest Control 183

13 Using AI Robotics for Soil Analysis and Fertility Management in Agriculture 199

14 Computational Intelligence and IoT in Transforming Agricultural Environmental Control 213

15 Real-time Monitoring and Quality Evaluation System of Fruits and Vegetables Using Image Processing 227

16 Computational Intelligence and Image Processing in Quality Evaluation of Agricultural Products 245

Index 259

Subject Areas: Electronics & communications engineering [TJ]
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