Smart Agriculture: A Compendium of Image-Based Learning Algorithms for Plant Leaf Diseases

In the lives of humans, agriculture is incredibly vital and is a backbone of every national economy. Agriculture in India is crucial because of the nation's speedy population growth and increased food consumption. Plant leaf diseases are a major cause of decreased yield and lower farmer revenue. Experts are currently putting great effort into creating a system that can recognize plant diseases automatically. The existence of bacterial, viral, and fungal infections exerts a substantial influence on reduced crop yields. Early diagnosis of plant leaf diseases is essential since they influence the growth of the particular species. The use of Artificial Intelligence is growing across many sectors to automate tasks and increase productivity. Plant leaf diseases have been identified and categorized using numerous Machine Learning models, however, recent progress in a subset of Machine Learning known as Deep Learning appear to offer tremendous promise for improved accuracy in this area of research. In this research study, various studies on plant leaf diseases are analyzed based on significant parameters like dataset used, plant names, different Machine Learning and Deep Learning models utilized, different disease types detected and overall accuracy achieved by the model. Even though numerous studies have already produced plant disease detection systems the proposed technique with convolutional neural networks (CNN) performs better.