Open AccessSegmentation of Affected Crops using Deep Learning
Author(s) -
S. Hemavathi,
Karthikeyan Velmurugan
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.e1052.0785s319
Subject(s) - pest analysis , agricultural engineering , deep learning , artificial intelligence , pesticide , agriculture , segmentation , fertilizer , computer science , machine learning , agronomy , engineering , biology , ecology , botany
Deep Learning technology can accurately predict the presence of diseases and pests in the agricultural farms. Upon this Machine learning algorithm, we can even predict accurately the chance of any disease and pest attacks in future For spraying the correct amount of fertilizer/pesticide to elimate host, the normal human monitoring system unable to predict accurately the total amount and ardent of pest and disease attack in farm. At the specified target area the artificial percepton tells the value accurately and give corrective measure and amount of fertilizers/ pesticides to be sprayed.