Abstract
The paper aims to carry out a systematic literature review to determine what computer vision techniques are prevalent in the field of precision agriculture, specifically for weed control. The review also noted what situations the techniques were best suited to and compared their various efficacy rates. The review covered a period between the years 2011 to 2022. The study findings indicate that computer vision in conjunction with machine learning and particularly Convolutional Neural Networks were the preferred options for most researchers. The techniques were generally applicable to all situations farmers may face themselves with a few exceptions, and they showed high efficacy rates across the board when it came to weed detection and control.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
