Segmentation of Affected Crops using Deep Learning
S. Hemavathi1, K. Jayasakthi Velmurugan2
1S.Hemavathi, Department of Computer Science and Engineering, Sri Sairam Engineering College, Chennai (Tamil Nadu), India.
2K.Jayasakthi Velmurugan, Department of Computer Science and Engineering, Jeppiaar Engineering College, Chennai (Tamil Nadu), India.
Manuscript received on 25 August 2019 | Revised Manuscript received on 01 September 2019 | Manuscript Published on 14 September 2019 | PP: 232-234 | Volume-8 Issue-5S3, July 2019 | Retrieval Number: E10520785S319/19©BEIESP | DOI: 10.35940/ijeat.E1052.0785S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Deep Learning, Perception, Host.
Scope of the Article: Deep Learning