Abstract

This article considers the main problems that are currently identified in the Russian Federation during the implementation of the project “Digital agriculture”. There is a selection of development trends of modern agriculture in the Russian Federation, where such digital technologies as big data, the Internet of Things, robotics, artificial intelligence are implemented. The authors have analyzed current agricultural research areas that conduct studies and implement various methods using deep machine learning and computer vision technologies. Attention is focused on the main tasks that, according to the authors, can solve various problems by implementing computer vision technology in crop production. Conclusions are also made about the representation and implementation of this technology in animal husbandry and fish farming. The team of authors presents a developed device for ultrasonic repelling of synanthropic mammals, describing the possibility of detecting a synanthropic organism, and shares research on the influence of ultrasonic signals on the behavior of mink. The article defines further areas of the practical application of deep learning neural networks in fish farming to solve applied problems that can be solved solely with the usage of computer vision technology.KeywordsComputer visionMovementAquaculture netImage processingColor space conversionActive contourUltrasoundUltrasound deviceMink

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