Deep Learning for Sustainable Agriculture reviews the fundamental concepts of gathering, processing and analyzing different deep learning models, along with a review of methods that can be used in this direction. The book also covers novel deep learning techniques for effective agriculture data management with standards laid by international organizations in related fields. The book is centered around evolving novel intelligent/deep learning models to solve the mitigation of agriculture. There are several deep learning models known that are used for weather forecasting, plant disease detection, underground water detection, quality of soil, and many more issues in agriculture.
- Introduces the novel deep learning models needed to address sustainable solutions for issues related to agriculture
- Provides reviews on the latest intelligent technologies and algorithms related to the state-of-the-art methodologies of monitoring and mitigation of sustainable agriculture
- Offers perspectives for the design, development and commissioning of intelligent applications
Dr. Ramesh Chandra Poonia is a Professor at the Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India. Recently completed his Postdoctoral Fellowship from CPS Lab, Department of ICT and Natural Sciences, Norwegian University of Science and Technology, Ålesund, Norway. He has received his Ph.D. degree in Computer Science from Banasthali University, Banasthali, India in July 2013. His research interests are Cyber-Physical Systems, Network Protocol Evaluation and Artificial Intelligence. He is Chief Editor of TARU Journal of Sustainable Technologies and Computing (TJSTC) and Associate Editor of the Journal of Sustainable Computing: Informatics and Systems, Elsevier. He also serves in the editorial boards of a few international journals. He is main author and co-author of 06 books and an editor of more than 25 special issue of journals and books including Springer, CRC Press – Taylor and Francis, IGI Global and Elsevier, edited books and Springer conference proceedings and has authored/co-authored over 65 research publications in peer-reviewed reputed journals, book chapters and conference proceedings.
Dr. Vijander Singh is working as Assistant Professor, Department of Computer Science and Engineering, Manipal University Jaipur, India. He received Ph.D. degree from Banasthali University, Banasthali, India, in April 2017. He has published 25 research papers in indexed journals and several book chapters for international publishers. He authored two books and handled/handling journals of international repute such as Taylor & Francis, Taru Publication, IGI Global, Inderscienc, etc. as guest editor. He is an associate editor of TARU Journal of Sustainable Technologies and Computing (TJSTC). He has organized several International Conferences, FDPs, and Workshops as a core team member of the organizing committee. His research area includes Machine Learning, Deep Learning, Precision Agriculture, and Networking.
Dr. Soumya Ranjan Nayak now holds the position of Assistant Professor in the School of Computer Engineering at Kalinga Institute of Industrial Technology (KIIT) Deemed to be University, located in Odisha, India. He obtained a Doctor of Philosophy (Ph.D) and Master of Technology (M.Tech) in Computer Science and Engineering under a scholarship provided by the Ministry of Human Resource Development (MHRD) of the Government of India. These degrees were earned at CET, BPUT Rourkela, India. Prior to this, he completed a Bachelor of Technology (B. Tech) and a Diploma in Computer Science and Engineering. He has authored over 150 articles that have been published in reputable international journals and conferences such as Elsevier, Springer, World Scientific, IOS Press, Taylor & Francis, Hindawi, Inderscience, IGI Global, and others. These publications have undergone a rigorous peer-review process. In addition to the aforementioned accomplishments, the individual has authored 16 book chapters, published 6 books, and obtained 7 Indian patents (with 4 patents being granted). Furthermore, they have secured 4 International patents, all of which have been granted. The researcher's current areas of focus encompass medical picture analysis and classification, machine learning, deep learning, pattern recognition, fractal graphics, and computer vision. The author's writings have garnered over 1500 citations, with an h-index of 24 and an i10-index of 63, as reported by Google Scholar. Dr. Nayak holds the position of an associate editor for several esteemed academic journals, including the Journal of Electronic Imaging (SPIE), Mathematical Problems in Engineering (Hindawi), Journal of Biomedical Imaging (Hindawi), Applied Computational Intelligence and Soft Computing (Hindawi), and PLOS One. He is currently fulfilling the role of a guest editor for special issues of renowned academic journals such as Springer Nature, Elsevier, and Taylor & Franchise. He has been affiliated as a reviewer for numerous esteemed peer-reviewed journals, including Applied Mathematics and Computation, Journal of Applied Remote Sensing, Mathematical Problems in Engineering, International Journal of Light and Electron Optics, Journal of Intelligent and Fuzzy Systems, Future Generation Computer Systems, Pattern Recognition Letters, and others. He has additionally held the Technical Program Committee Member position for several conferences of significant worldwide recognition.
