The digital transformation of agriculture has evolved various aspects of management into
artificial intelligent systems for the sake of making value from the ever-increasing data …

Precision Agriculture (PA) promises to boost crop productivity while reducing agricultural
costs and environmental footprints, and therefore is attracting ever-increasing interests in …

The agriculture industry is undergoing a rapid digital transformation and is growing powerful
by the pillars of cutting-edge approaches like artificial intelligence and allied technologies …

Convolutional neural network (CNN)-based deep learning (DL) is a powerful, recently
developed image classification approach. With origins in the computer vision and image …

Monitoring crops and weeds is a major challenge in agriculture and food production today.
Weeds compete directly with crops for moisture, nutrients, and sunlight. They therefore have …

Weed identification in vegetable plantation is more challenging than crop weed identification
due to their random plant spacing. So far, little work has been found on identifying weeds in …

In recent years unmanned aerial vehicles (UAVs) have emerged as a popular and cost-
effective technology to capture high spatial and temporal resolution remote sensing (RS) …

The problem of weeds in crops is a natural problem for farmers. Machine Learning (ML),
Deep Learning (DL), and Unmanned Aerial Vehicles (UAV) are among the advanced …

Site-specific weed management in Precision Agriculture is becoming a popular topic among
researchers and farmers. The objective of this study was to classify weeds and crop species …

Knowing precise location and having accurate information about weed species is a
prerequisite for developing an effective site-specific weed management (SSWM) system …