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Advances in environmental engineering and green technologies (AEEGT) book series.
Modern techniques for agricultural disease management and crop yield prediction / N. Pradeep, Sandeep Kautish, C.R. Nirmala, Vishal Goyal, Sonia Abdellatif, [editors]. — 1 online resource (xix, 291 pages) : illustrations (chiefly color. — (Advances in Environmental Engineering and Green Technologies (AEEGT) book series). — "eISSN: 2326-9170.". — <URL:http://elib.fa.ru/ebsco/2216958.pdf>.

Record create date: 8/8/2019

Subject: Agriculture — Data processing.; Agricultural innovations.; Precision farming.; Phytopathogenic microorganisms — Control.; Crop yields.; Agricultural innovations.; Agriculture — Data processing.; Crop yields.; Phytopathogenic microorganisms — Control.; Precision farming.

Collections: EBSCO

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"This book explores the current practices and widespread open challenges in the field of applications of computational techniques in smart agriculture. It also examines computational methods that will aid in agriculture disease management, weed detection, and crop yield prediction"--Provided by publisher.

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Table of Contents

  • Cover
  • Title Page
  • Copyright Page
  • Book Series
  • Editorial Advisory Board
  • Table of Contents
  • Detailed Table of Contents
  • Foreword
  • Preface
  • Acknowledgment
  • Chapter 1: Issues and Challenges in Smart Farming for Sustainable Agriculture
  • Chapter 2: Image Processing Techniques Aiding Smart Agriculture
  • Chapter 3: Expert System Design for Diagnosis of Diseases for Paddy Crop
  • Chapter 4: Deep Learning and Computer Vision in Smart Agriculture
  • Chapter 5: Computer Vision for Green Plant Segmentation and Leaf Count
  • Chapter 6: Automatic Data Acquisition and Spot Disease Identification System in Plants Pathology Domain
  • Chapter 7: Applications of Data Mining Techniques in Smart Farming for Sustainable Agriculture
  • Chapter 8: Agro Guardian
  • Chapter 9: A Study on Technology-LED Solutions for Fruit Grading to Address Post-Harvest Handling Issues of Horticultural Crops
  • Chapter 10: Optimized Data Mining Techniques for Outlier Detection, Removal, and Management Zone Delineation for Yield Prediction
  • Compilation of References
  • About the Contributors
  • Index

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