Computer Vision and Machine Learning in Agriculture, Volume 3

This book is as an extension of the previous two volumes on Computer Vision and Machine Learning in Agriculture. This volume 3 discusses solutions to the problems of agricultural production by rendering advanced machine learning including deep learning tools and techniques. The book contains 13 chapters that focus on in-depth research outputs in precision agriculture, crop farming, horticulture, floriculture, vertical farming, animal husbandry, disease detection, plant recognition, production yield, product quality, defect assessment, and overall automation through robots and drones. The topics covered in the current volume, along with the previous volumes, are comprehensive literature for both beginners and experienced in this domain.

Describes intelligent robots and drones Discusses research outputs in precision agriculture Presents applications of computer vision and machine learning (CV-ML) for better agricultural practices

Auteur

Dr. Jagdish Chand Bansal is Associate Professor (Senior Grade) at South Asian University, New Delhi, and Visiting Faculty at Mathematics and Computer Science, Liverpool Hope University, UK. Dr. Bansal obtained his Ph.D. in Mathematics from IIT Roorkee. Before joining SAU, New Delhi, he worked as an Assistant Professor at ABV-Indian Institute of Information Technology and Management Gwalior and BITS Pilani. His primary area of interest is swarm intelligence and nature-inspired optimization techniques. Recently, he proposed a fission-fusion social structure-based optimization algorithm, spider monkey optimization (SMO), which is being applied to various problems in the engineering domain. He has published more than 70 research papers in various international journals/conferences. He is the Section Editor (editor-in-chief) of the journal MethodsX published by Elsevier. He is the Series Editor of the book series Algorithms for Intelligent Systems (AIS), Studies in Autonomic, Data-drivenand Industrial Computing (SADIC), and Innovations in Sustainable Technologies and Computing (ISTC) published by Springer. He is also an Associate Editor of Engineering Applications of Artificial Intelligence (EAAI) and ARRAY published by Elsevier. He is the General Secretary of the Soft Computing Research Society (SCRS). He has also received Gold Medal at UG and PG levels.

Prof. Mohammad Shorif Uddin completed his Doctor of Engineering (Ph.D.) at Kyoto Institute of Technology, Japan, in 2002, Master of Technology Education at Shiga University, Japan, in 1999, Bachelor of Electrical and Electronic Engineering at Bangladesh University of Engineering and Technology (BUET) in 1991, and also Master of Business Administration (MBA) from Jahangirnagar University in 2013. He began his teaching career as Lecturer in 1991 at Chittagong University of Engineering and Technology (CUET). In 1992, he joined the Computer Science and Engineering Department of Jahangirnagar University, and at present, he is a Professor in this department. He served as Chairman of the Computer Science and Engineering Department of Jahangirnagar University from June 2014 to June 2017 and Teacher-in-Charge of the ICT Cell of Jahangirnagar University from February 2015 to April 2023. He worked as an Adviser at ULAB from September 2009 to October 2020 and at Hamdard University Bangladesh from November 2020 to November 2021. He undertook postdoctoral research at Bioinformatics Institute, Singapore, Toyota Technological Institute, Japan, and Kyoto Institute of Technology, Japan, Chiba University, Japan, Bonn University, Germany, Institute of Automation, Chinese Academy of Sciences, China. His research is motivated by applications in the fields of artificial intelligence, machine learning, computer vision, and image security. He holds two patents for his scientific inventions and has published around 200 research papers in international journals and conference proceedings. In addition, he edited a good number of books and wrote many chapters. He delivered a remarkable number of keynotes and invited talks and also acted as General Chair or TPC Chair or Co-chair of many international conferences. He received the Best Paper Award from the International Conference on Informatics, Electronics and Vision (ICIEV2013), Dhaka, Bangladesh, and the Best Presenter Award from the International Conference on Computer Vision and Graphics (ICCVG 2004), Warsaw, Poland. He was the Coach of Janhangirnagar University ACM ICPC World Finals Teams in 2015 and 2017 and supervised a good number of doctoral and master theses. He is a Fellow of IEB and BCS, a Senior Member of IEEE, and an Associate Editor of IEEE Access.

Texte du rabat

This book is as an extension of the previous two volumes on Computer Vision and Machine Learning in Agriculture . This volume 3 discusses solutions to the problems of agricultural production by rendering advanced machine learning including deep learning tools and techniques. The book contains 13 chapters that focus on in-depth research outputs in precision agriculture, crop farming, horticulture, floriculture, vertical farming, animal husbandry, disease detection, plant recognition, production yield, product quality, defect assessment, and overall automation through robots and drones. The topics covered in the current volume, along with the previous volumes, are comprehensive literature for both beginners and experienced in this domain.

Contenu

Leveraging Computer Vision for Precision Viticulture.- An intelligent vision-guided framework of the unmanned aerial system for precision agriculture.- Data Preprocessing Techniques for Supervised Learning on Agricultural Data.- Strawberries Maturity Level Detection Using Convolutional Neural Network (CNN) and Ensemble Method.- Recognition of Fresh and Rotten Fruits through the Development of a Dataset.