Proceedings of the Second International Conference on Emerging Trends in Engineering (ICETE 2023)

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Detection of Weeds by Using Machine Learning

Authors
P. Kavitha Reddy1, *, R. Anirudh Reddy1, Mail Abhishek Reddy1, Katkam Sai Teja1, K. Rohith1, K. Rahul1
1B.V. Raju Institute of Technology, Medak, Telangana, India
*Corresponding author. Email: Kavithareddy.p@bvrit.ac.in
Corresponding Author
P. Kavitha Reddy
Available Online 9 November 2023.
DOI
10.2991/978-94-6463-252-1_89How to use a DOI?
Keywords
Input images; python open CV; weed detection; convolution neural network (CNN); Machine learning
Abstract

The foundation of our nation is agriculture. India’s economy is mostly based on agriculture. So many people dependent on the agriculture in the country. The people involved in agriculture is reduce as threats there increase. Weeds are the one of the main things which is affecting the crops in agriculture fields. In this research, we present a straight forward image processing technique that enables quick and easy weed detection by scrutinizing the input image. Photos of plants from various crop are taken with a digital camera, and the images are used to classify the affected region in the plants. Here we have used python-3.1 version and open CV. In this image processing deep convolutional neural network (CNN) architecture is developed to implement this classification with improved accuracy by increasing the deep layers as compared to the existing CNN. We will follow this method for the detection or recognition of the weeds in the crops. Where it will detect multiple types of weeds.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the Second International Conference on Emerging Trends in Engineering (ICETE 2023)
Series
Advances in Engineering Research
Publication Date
9 November 2023
ISBN
10.2991/978-94-6463-252-1_89
ISSN
2352-5401
DOI
10.2991/978-94-6463-252-1_89How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - P. Kavitha Reddy
AU  - R. Anirudh Reddy
AU  - Mail Abhishek Reddy
AU  - Katkam Sai Teja
AU  - K. Rohith
AU  - K. Rahul
PY  - 2023
DA  - 2023/11/09
TI  - Detection of Weeds by Using Machine Learning
BT  - Proceedings of the Second International Conference on Emerging Trends in Engineering (ICETE 2023)
PB  - Atlantis Press
SP  - 882
EP  - 892
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-252-1_89
DO  - 10.2991/978-94-6463-252-1_89
ID  - KavithaReddy2023
ER  -