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

Year 2023, Volume: 11 Issue: 2, 581 - 600, 01.06.2023

Damla Karagozlu , John Karima Macharıa Tolgay Karanfiller

https://doi.org/10.36306/konjes.1097969

Cited By: 1

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

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

Abstract

Bu çalışma, hassas tarım alanında yabancı ot kontrolü için yaygın kullanılan bilgisayarlı görme tekniklerini ortaya koymak amacıyla sistematik literatür taraması yapmayı amaçlamaktadır. Gerçekleştirilen literatür incelemesinde ayrıca bilgisayarlı görme tekniklerinin verimli olduğu durumlar da açıklanmaktadır. Çalışma kapsamını 2011 ile 2022 yılları arasındaki literatür çalışmaları oluşturmaktadır. Çalışma bulguları, makine öğrenimi ve özellikle Konvolüsyonel Sinir Ağları ile birlikte bilgisayarlı görmenin birçok araştırmacı tarafından tercih edilen seçenekler olduğunu göstermektedir. Bilgisayarlı görme tekniklerinin genel olarak çiftçilerin karşılaşabilecekleri tüm durumlara uygulanabilirliği, yabancı ot tespiti ve kontrolü konularında yüksek etkinlik oranları gösterdiği sonuçları elde edilmiştir.

Keywords

Computer Vision, Machine Vision, Precision Agriculture, Smart Farming, Weed Control

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