Identification of Plant Disease in Leaves, using Deep Neural Networks
Hemalatha N1,  Anusha T A2,  Asha Nair3

1N Hemalatha, Associate Professor, Department of IT and Bioinformatics, AIMIT, St Aloysius College, Mangalore (Karnataka), India.
2Anusha T A, Department of Bioinformatics, St Aloysius College, Mangalore (Karnataka), India.
3Asha Nair, Pursuing M.SC, Big Data Analytics, St. Aloysius of Science & Technology, Mangalore (Karnataka), India.
Manuscript received on 13 February 2020 | Revised Manuscript received on 20 February 2020 | Manuscript Published on 28 February 2020 | PP: 18-21 | Volume-8 Issue-5S February 2020 | Retrieval Number: E10040285S20/2020©BEIESP | DOI: 10.35940/ijrte.E1004.0285S20
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Abstract: Plant diseases have become a concern as they can lead to a significant reduction in both the quality and quantity of agricultural products. Immediate identification of plant diseases is a key research topic as it can prove useful in the monitoring of large crop fields and thus automatically identify the signs of pathogens as soon as they appear on plant leaves. The proposed efficient algorithm could successfully identify and recognize the diseases under investigation and model could achieve an accuracy of 95.18.
Keywords: Tomato Leaf Diseases, Potato Leaf Diseases, Pepper Leaf Diseases.
Scope of the Article: Deep Learning