IDENTIFICATION OF PESTS AND DISEASES USING ALEX-NET

Authors

  • DEVENDRA MORANKAR Department of E&TC, PICT, Pune, India
  • DEEPAK M.SHINDE Department of E&TC, PICT, Pune, India
  • SUVIDYA R PAWAR Department of E&TC, PICT, Pune, India

Keywords:

Image Processing,, Alex-Net, Machine Learning

Abstract

One of the essential tasks of agriculture is to identify epidemic because these diseases not only harm the production but can cause major environmental catastrophe. At least insecticides need to develop some effective techniques and solutions. It can be adapted to farming too for productivity, using agricultural science besides various image analysis techniques. We can use manpower to control the effect of pests. Some system reduces human effort and mistakes through automatic surveillance and this technique is a work in progress. In this project, the category of infection is caused by insect and leaf image. Then we have methods of an image processing which is used in agricultural management. Mobile is used for image editing and the same camera is used for a computer program designed to allow a computer user to interact easily with the help of Internet Protocol. These characteristics of the foliage structure are calculated by considering the gray-level co-event matrix. In the pattern recognition technique it is processed for training, validation and testing and its accuracy is 71.6%. Alex-Net is have been utilized for practice and classifying images. Alex-Net uses the Interactive Transfer Learning Network to arrange a new collection of images. This paper provides a fully automated advanced towards to the testimonial and assortment of pest diseases and their pests. This is especially useful for farmers likewise citizens who are doing gardening in the area of their homes.

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Published

2021-03-10

Issue

Vol. 7 No. 4 (2020): IJIERT

Section

Articles

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How to Cite

DEVENDRA MORANKAR, DEEPAK M.SHINDE, & SUVIDYA R PAWAR. (2021). IDENTIFICATION OF PESTS AND DISEASES USING ALEX-NET. International Journal of Innovations in Engineering Research and Technology, 7(4), 1-9. https://repo.ijiert.org/index.php/ijiert/article/view/2089