Classification of Plant leaf diseases: A Deep Learning Method
Taruna Sharma1, Ruchi Mittal2
1Taruna Sharma, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India.
2Ruchi Mittal*, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India.
Manuscript received on October 19, 2019. | Revised Manuscript received on 29 October, 2019. | Manuscript published on November 10, 2019. | PP: 5195-5197 | Volume-9 Issue-1, November 2019. | Retrieval Number: A9230119119/2019©BEIESP | DOI: 10.35940/ijitee.A9230.119119
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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: For the continuous existence of human life, agriculture plays a vital role due to the dependency of lives of people on it for production of food. In order to meet high production rate, precision farming is required. Presently, substantial developments attained “in the field of image processing and recognition” which has being a foremost challenge earlier in the practice of Precision farming. The reduction in the growth, quality and quantity of plants is due to expansion of plant diseases.The survey literature confers various plant leaf diseases and their detections during different phases through various state of art machine and deep learning techniques. The particular emphasis in this paper is on detection and classification of plant “leaf diseases” through deep “convolutional neural networks algorithms.
Keywords: Classification, Plant Leaf, Production of foof, Convolutional.
Scope of the Article: Classification