Recently, agriculture has gained much attention regarding automation by artificial
intelligence techniques and robotic systems. Particularly, with the advancements in machine …

Weeds are amongst the most impacting abiotic factors in agriculture, causing important yield
loss worldwide. Integrated Weed Management coupled with the use of Unmanned Aerial …

Highlights•A convolutional neural network is designed to determine the species of
seedlings.•The system is trained and tested on images of 22 plant species.•The images are …

The discipline of weed science is at a critical juncture. Decades of efficient chemical weed
control have led to a rise in the number of herbicide-resistant weed populations, with few …

Robotics and variable rate technology (VRT) have shown great potential for site-specific
weed management (SSWM), but these technologies face several challenges like accurate …

Crop productivity is readily reduced by competition from weeds. It is particularly important to
control weeds early to prevent yield losses. Limited herbicide choices and increasing costs …

In precision agriculture, the accurate segmentation of crops and weeds in agronomic images
has always been the center of attention. Many methods have been proposed but still the …

Highlights•A new type of vertical rotary mechanical weeding system was
developed.•Detection is conducted with deep learning techniques to create protected and …

Highlights•A real-time in-row weed-crop detection and classification algorithm was
proposed.•A novel crop signaling technique was introduced to distinguish crops from …

The excessive consumption of herbicides has gradually led to the herbicide resistance weed
phenomenon. Managing herbicide resistance weeds can only be explicated by applying …