Deep Learning for Sustainable Agriculture

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