Deep learning-based decision support system for weeds detection in wheat fields
نویسندگان
چکیده
<span>In precision farming, identifying weeds is an essential first step in planning integrated pest management program cereals. By knowing the species present, we can learn about types of herbicides to use control them, especially non-weeding crops where mechanical methods that are not effective (tillage, hand weeding, and hoeing mowing). Therefore, using deep learning based on convolutional neural network (CNN) will help automatically identify then intelligent system comes achieve a localized spraying avoiding their large-scale use, preserving environment. In this article propose smart object detection models, implemented Raspberry, seek presence relevant objects (weeds) area (wheat crop) real time classify those for decision support including spot spray with chosen herbicide accordance weed detected.</span>
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ژورنال
عنوان ژورنال: International Journal of Power Electronics and Drive Systems
سال: 2022
ISSN: ['2722-2578', '2722-256X']
DOI: https://doi.org/10.11591/ijece.v12i1.pp816-825