COMPUTER VISION IN PRECISION AGRICULTURE FOR WEED CONTROL: A SYSTEMATIC LITERATURE REVIEW

Authors : Damla KARAGOZLU, John Karima MACHARIA, Tolgay KARANFİLLER

Pages : 581-600

Doi:10.36306/konjes.1097969

View : 72 | Download : 80

Publication Date : 2023-06-01

Article Type : Review Paper

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.
Keywords : Computer Vision, Machine Vision, Precision Agriculture, Smart Farming, Weed Control