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This special issue of Agronomy focuses on the applications of deep learning in smart agriculture. It aims to present the state-of-the-art and original analytical methods based on deep learning for converging diverse advanced agro-environmental data from machinery, drone, airborne, and satellite sensors into information relevant to various agronomy sciences applications. Research papers that examine the latest developments in concepts, methods, techniques, and case studies related to smart agriculture are included.
