Artificial intelligence (AI) has long been applied in agriculture and has become especially prevalent in recent years. AI especially deep learning technique have progressed to have much stronger learning ability to learn more useful features to handle even more complicated task in the field of precision agriculture. Challenges in agriculture such as disease, infestation, inadequate irrigation and soil treatment, and poor crop management have brought about crop losses and adverse effects on the environment. Not to mention, the ever-increasing demand of agricultural product due to the increasing global population and the limited amount of arable land. To be overcome, those challenges need innovative approaches, ones that could benefit from AI’s flexibility, accuracy, cost-effectiveness, and generally superior efficiency. AI technology whose aim is to mimic the ability of humans to solve problems especially in decision making enables agricultural activities to be done more efficiently while reducing human interference. The use of AI in agriculture has evolved from the application of fuzzy logic, then into machine learning and deep learning. Some deep learning methods that have been ap
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