Weed Identification using Regional Convolutional Neural Network

Authors

  • SriLakshmi Polavarapu Student, M.Tech. Integrated Software Engineering, Vellore Institute of Technology, Chennai, India

Keywords:

Convolution Neural Network, Image Data Generator, Regional Convolution Neural Network, fine tuning, Support Vector Machine, VGG16

Abstract

In ancient days most of the people selected farming as their occupation. For that, people started to cultivate crops in their fields. But there were days where people had to fight against the invasion of weeds in their fields. Weeds that are unwanted plants present around a good plant. To overcome this problem people started to remove the weeds manually by cutting them very close to the ground. Later when days passed by people started using pesticides and some form of chemicals to cut them off. As the technology has developed and the process of removing weed by using the above practices were very much time consuming. Usage of chemicals for controlling unwanted plants has become a con for the crops, as it contains some harmful side effects when sprayed on a healthy plant. Due to this many people have moved to an advanced technique of deep learning. Convolution Neural Network have become popular and also a good way to remove weeds.

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Published

23-01-2022

How to Cite

[1]
S. Polavarapu, “Weed Identification using Regional Convolutional Neural Network”, IJRESM, vol. 5, no. 1, pp. 106–109, Jan. 2022.

Issue

Section

Articles