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 …

Aiming at the shortcomings of the existing navigation line extraction algorithm for corn
spraying robot in complex farmland environment, such as poor extraction effect and poor …

Highlights•Modifiy a deep learning model to detect rice seedlings under different
conditions.•Extract the seedling strip lines of straight-curved rice seedling rows.•Seeding row …

Field crops are usually planted in rows, and accurate identification and extraction of crop
row centerline is the key to realize autonomous navigation and safe operation of agricultural …

Recognition of rice seedling rows under machine operation is affected by many factors such
as light conditions, duckweed, weeds, and blur caused by machine vibration. Recognition of …

This review paper addresses the critical need for advanced rice disease detection methods
by integrating artificial intelligence, specifically convolutional neural networks (CNNs). Rice …

This study focuses on real-time detection of maize crop rows using deep learning
technology to meet the needs of autonomous navigation for weed removal during the maize …

The increase in the number of tillers of rice significantly affects grain yield. However, this is
measured only by the manual counting of emerging tillers, where the most common method …

Weeds are unwanted plants that grow in farmlands and compete with nutrients and sunlight
for growth. If not removed, they could obstruct the growth of crops causing reduction in crop …

Autonomous navigation in farmlands is one of the key technologies for achieving
autonomous management in maize fields. Among various navigation techniques, visual …