Open AccessPaddy Crop Disease Prediction- A Transfer Learning Technique
Author(s) -
Siddharth Swarup Rautaray,
Manjusha Pandey,
Mahendra Kumar Gourisaria,
Ritesh Kumar Sharma,
Sujay Das
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.f7782.038620
Subject(s) - agriculture , productivity , computer science , business , work (physics) , risk analysis (engineering) , natural resource economics , microbiology and biotechnology , engineering , economics , biology , ecology , economic growth , mechanical engineering
Agriculture is the spinal cord of the human society because it is an essential need of every organism that exists in this planet. Paddy cultivation is very significant so far as humans are concerned, especially in the Asian subcontinent. Since human beings are considered as one of the most intelligent species, it is necessary for us to protect the importance and productivity of agriculture. Since the entry of the IT industry, there has been some improvement in the productivity in the agriculture. It has done a lot of work in the healthcare of the agriculture. Deep learning is a buzzword in the IT sector. This buzzword has helped a lot to improve the productivity of in the agriculture field. In the recent past, due to excessive use of human made chemicals and pesticides, the diseases in plants have increased in a higher rate. These diseases in agricultural plants cannot be ignored as it can be dangerous in later stages. Also due to lack of technical knowledge, sometimes it becomes difficult to detect these diseases. So, this paper presents a model for detecting the disease present in the paddy plant. The model uses transfer learning approach which is a paradigm of solving deep learning problems in an efficient manner. This model also finds the probability of the occurrence of disease which can be helpful to take some vital decisions related to plant’s health.