Computer Vision and Machine Learning in Agriculture

dc.contributor.authorM., Raval
dc.contributor.authorS., Chaudhary
dc.contributor.authorJ., Adinarayana
dc.date.accessioned2023-03-30T08:46:19Z
dc.date.available2023-03-30T08:46:19Z
dc.date.issued2021-11
dc.descriptionPage: 97 - 126en_US
dc.description.abstractThis book aims to address emerging challenges in the field of agriculture and natural resource management using the principles and applications of data science (DS). The book is organized in three sections, and it has fourteen chapters dealing with specialized areas. The chapters are written by experts sharing their experiences very lucidly through case studies, suitable illustrations and tables. The contents have been designed to fulfil the needs of geospatial, data science, agricultural, natural resources and environmental sciences of traditional universities, agricultural universities, technological universities, research institutes and academic colleges worldwide. It will help the planners, policymakers and extension scientists in planning and sustainable management of agriculture and natural resources. The authors believe that with its uniqueness the book is one of the important efforts in the contemporary cyber-physical systems.
dc.identifier.issn978-981-16-5847-1
dc.identifier.urihttps://link.springer.com/book/10.1007/978-981-16-5847-1
dc.publisherSingapore: Springeren_US
dc.titleComputer Vision and Machine Learning in Agricultureen_US
dc.title.alternativeData Science in Agriculture and Natural Resource Managementen_US
dc.typeOtheren_US

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