PLANT DISEASE DETECTION USING DEEP LEARNING

Plants are becoming a significant energy source and the main cause of the global warming issue. In plant systems, the harm caused by endemic, re-emerging, and emerging diseases is significant and may result in financial loss. Furthermore, crop diseases both directly and indirectly contribute to environmental harm and the development of infectious diseases in humans. Since these illnesses are spreading throughout the world, they are harming not only the plant's ability to operate normally but also the plant's financial situation by drastically lowering the amount of crops that are grown. Many diseases cause crop output to lose its quality; occasionally, these diseases even manifest themselves imperceptibly. Farmers predict illnesses based on their personal experience, but this is incorrect. Agriculture now serves far more purposes than just feeding the world's expanding population. In India, where agriculture supports over 70% of the population, this is crucial. This indicates that it feeds a sizable population. Plant diseases can have a direct or indirect impact on human health as well as the economy. We require a quick, automatic method to identify these plant diseases. Various methods of digital image processing are used to analyze diseases. In order to identify plant diseases, we conducted a survey on several digital image processing methods in this research.