Convolutional Neural Networks for Use in Weed Detection

Authors

  • P Jeeva  Department of MCA, Sri Venkateswara College of Engineering and Technology, Chittoor, Andhra Pradesh, India
  • S Jayaprakash  Department of MCA, Sri Venkateswara College of Engineering and Technology, Chittoor, Andhra Pradesh, India
  • S. Srinath  Department of MCA, Sri Venkateswara College of Engineering and Technology, Chittoor, Andhra Pradesh, India
  • Dr. Subrata Chowdhury  Associate Professor, Department of MCA, Sri Venkateswara College of Engineering and Technology, Chittoor, Andhra Pradesh, India

Keywords:

Weed Detection, Deep Learning, CNN.

Abstract

Today, weed detection and plant detection in plants are increasingly challenging. Vegetable planting weeds have not received much attention thus far. Although the differences in weed species are significant, traditional methods for weed identification focused mostly on directly identifying weed. This work proposes an alternative approach that combines deep learning with image technologies. The dataset was initially trained using the CNN model. Once the training is finished, we can identify and predict whether the input image is a crop or a weed.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2022-12-30

Issue

Volume 8, Issue 6, November-December-2022

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
P Jeeva, S Jayaprakash, S. Srinath, Dr. Subrata Chowdhury, " Convolutional Neural Networks for Use in Weed Detection" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 6, pp.95-103, November-December-2022.