In the face of increasing agricultural demands and environmental concerns, the effective
management of weeds presents a pressing challenge in modern agriculture. Weeds not only …

Crop protection is a key activity for the sustainability and feasibility of agriculture in a current
context of climate change, which is causing the destabilization of agricultural practices and …

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

The past decade has witnessed the rapid development and adoption of machine and deep
learning (ML & DL) methodologies in agricultural systems, showcased by great successes in …

The presence of weeds poses a common and persistent problem in crop cultivation,
affecting both yield and overall agricultural productivity. Common solutions to the problem …

Weeds challenge crops by competing for resources and spreading diseases, impacting crop
yield and quality. Effective weed detection can enhance herbicide application, thus reducing …

Recent advancements in deep learning (DL)-based model optimization techniques have
resulted in better weed identification accuracy. However, optimizing these models to identify …

This review paper highlights about the important applications of Artificial Intelligence (AI)
and in vitro micropropagation of Cannabis. Cannabis micropropagation has largely been an …

Competition for nutrients between intra-row weeds and cultivated vegetables is a major
contributor to reduced crop yields. Compared with manual weeding, intelligent robots can …

Deep learning (DL) inspired models have achieved tremendous success in locating target
weed species through bounding-box approach (single-stage models) or pixel-wise semantic …