This paper is published in Volume-10, Issue-5, 2024
Area
Crops And Weeds Detection System Using Machine Learning
Author
Shrusti Jasani, Spandan Kathiriya, Sneh Patel, Ms. Manisha Vasava
Org/Univ
Drs. Kiran and Pallavi Patel Global University, Vadodara, India
Keywords
Agriculture, Weeds, Crops.
Citations
IEEE
Shrusti Jasani, Spandan Kathiriya, Sneh Patel, Ms. Manisha Vasava. Crops and Weeds Detection System using Machine Learning, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Shrusti Jasani, Spandan Kathiriya, Sneh Patel, Ms. Manisha Vasava (2024). Crops and Weeds Detection System using Machine Learning. International Journal of Advance Research, Ideas and Innovations in Technology, 10(5) www.IJARIIT.com.
MLA
Shrusti Jasani, Spandan Kathiriya, Sneh Patel, Ms. Manisha Vasava. "Crops and Weeds Detection System using Machine Learning." International Journal of Advance Research, Ideas and Innovations in Technology 10.5 (2024). www.IJARIIT.com.
Shrusti Jasani, Spandan Kathiriya, Sneh Patel, Ms. Manisha Vasava. Crops and Weeds Detection System using Machine Learning, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Shrusti Jasani, Spandan Kathiriya, Sneh Patel, Ms. Manisha Vasava (2024). Crops and Weeds Detection System using Machine Learning. International Journal of Advance Research, Ideas and Innovations in Technology, 10(5) www.IJARIIT.com.
MLA
Shrusti Jasani, Spandan Kathiriya, Sneh Patel, Ms. Manisha Vasava. "Crops and Weeds Detection System using Machine Learning." International Journal of Advance Research, Ideas and Innovations in Technology 10.5 (2024). www.IJARIIT.com.
Abstract
Weeds are one of the most harmful agricultural pests for crops. For the waste of crops, Weeds are highly responsible. For the solution of this problem research community as build up a crops and weeds detection system. This technology is build up by using Machine learning. In this paper, we present a literature review on current state-of-the-art ML techniques for weed detection. Our study presents a detailed analysis of ML.