Weeds are one of the most important factors affecting agricultural production. The waste and
pollution of farmland ecological environment caused by full-coverage chemical herbicide …

Significant advances in the field of digital image processing have been achieved in recent
years using deep learning, which has significantly exceeded previous methods. Deep …

Features are the vital factor for image classification in the field of machine learning. The
advancement of deep convolutional neural network (CNN) shows the way for identification …

Crop row detection is one of the foundational and pivotal technologies of agricultural robots
and autonomous vehicles for navigation, guidance, path planning, and automated farming in …

Weed control in paddy fields is a critical agronomic practice for enhancing rice yield, in
which mechanical weed control is widely used due to its high weed control rate and …

In order to improve the efficiency and reduce high cost for seedlings sorting in the raising
process of hydroponic lettuce seedlings, we propose an automatic detection method for …

Highlights•Proposing a crop row detection method based on YOLO-R object detection
algorithm.•Ghostnet and Focal Loss are used in YOLO-R to perform better and faster.•Use …

Background Weed recognition is key for automatic weeding, which is a challenging problem.
Weed recognition is mainly based on different features of crop images. The extracted image …

Research is being extensively conducted on using deep learning in the field of crop and
weed segmentation based on images captured with a camera. However, the segmentation …