Deep Learning Techniques used in Detecting and Classifying Images of Multi Crop Leaf Diseases

Health is very important factor in the life of human beings. Qualitative or healthy food is also playing an important role in healthy human beings. Healthy food which rich in healthy nutrients will get only from healthy crop fields.so indirectly different crop plants have important role in human beings’ life. We all human beings require food for living our daily life. Food grains production quality and quantity both may affected by bad weather conditions, heavy rain, floods, drought, aridity and plant diseases. We can’t control different bad weather conditions which affect the quantity and quality of crop productions. Skilful farmers rarely notice plants with the opened eye whereas disease, but this method is often indefinite and can take a long time. Controlling damaged leaves while crops are developing is a critical step. Early disease identification, categorization and analysis of sick leaves, as well as potential remedies, can boost crop productivity. Farmer understood the importance and use of artificial intelligence in agriculture field. Several machine learning (ML) as well as deep learning (DL) techniques are developed and explore by many researchers, and oftentimes they also got significant results in both cases. By Inspiring those existing work, here this paper studied and compared different deep learning techniques from different researchers for studying further better result in multi crop leaf disease classification and detection