Open AccessDeep Learning Models for Leaf Disease Detection for Crops in Agriculture Field : A Survey
Author(s) -
Sunidhi Shrivastava,
Pankaj Gugnani,
Neha Garg
Publication year - 2020
Publication title -
international journal of scientific research in computer science, engineering and information technology
Language(s) - English
Resource type - Journals
ISSN - 2456-3307
DOI - 10.32628/cseit20636
Subject(s) - deep learning , agriculture , artificial intelligence , field (mathematics) , computer science , production (economics) , machine learning , food processing , identification (biology) , image processing , precision agriculture , plant disease , agricultural engineering , crop production , data science , image (mathematics) , microbiology and biotechnology , engineering , mathematics , geography , chemistry , botany , food science , archaeology , biology , pure mathematics , economics , macroeconomics
Crop and plant Diseases are the common problems in the food production fields. This is necessary for the improvement of the food production in agriculture and for fulfills the need of the society to solve these problems. In India most of the part of the country based on the production of food as a tradition. To solve these problems some advanced image processing, machine learning, computer vision etc. advancements included. This survey research on the identification of all that kind of technologies and the existing work also has done using them. How many kinds of models are proposed and what amount of success they have achieved by utilizing them. Image processing techniques provides the automatic disease detection technique to detect and identify the diseases in plants. Deep learning techniques are very good at prediction of the growth of plan and possibility of having disease within them. A comparison study also performed of several machine and deep learning techniques based on their accuracy.