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Statistics report
Apr
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
  Journal Paper


Paper Title :
Study an Image Processing based Approach to Identification of Banana Plant Disease using DIY Built F450 Drone

Author :Aravinthara Kumaran, Balu Ramu

Article Citation :Aravinthara Kumaran ,Balu Ramu , (2022 ) " Study an Image Processing based Approach to Identification of Banana Plant Disease using DIY Built F450 Drone " , International Journal of Advances in Science, Engineering and Technology(IJASEAT) , pp. 146-152, Volume-10,Issue-3

Abstract : Abstract - In this research paper is an image processing-based approach is being proposed and used for banana plant disease detection and locating using Aruco Marker ID tags and a DIY-Built F450 Drone at very low cost. Author tests our results on three diseases which effect on banana crops; they are: Cordana, Pestalotiopsis and Sigatoka. The proposed approach is image processing based and is much supported Convolutional Neural Network (CNN) adopting AlexNet Architecture. The approach consists of 6 main phases; capturing images of plants with their individual Aruco Tag ID to Google Drive database from drone, data pre-processing, images are segmented using RGB to HSI conversion, applying mask to K-means clustering on the images, extracting feature from data and training Neural Network Model. Keywords - Neural Network, Convolutional Neural Network, Plant Disease, Image Processing

Type : Research paper

Published : Volume-10,Issue-3


DOIONLINE NO - IJASEAT-IRAJ-DOIONLINE-19032   View Here

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