During the last few years, Unmanned Aerial Vehicles (UAVs) technologies are widely used
to improve agriculture productivity while reducing drudgery, inspection time, and crop …

In agricultural image analysis, optimal model performance is keenly pursued for better
fulfilling visual recognition tasks (eg, image classification, segmentation, object detection …

The rapid advances in Deep Learning (DL) techniques have enabled rapid detection,
localisation, and recognition of objects from images or videos. DL techniques are now being …

The three previous industrial revolutions profoundly transformed agriculture industry from
indigenous farming to mechanized farming and recent precision agriculture. Industrial …

As an important research topic in recent years, semantic segmentation has been widely
applied to image understanding problems in various fields. With the successful application …

Abstract Internet of Things (IoT) and Unmanned Aerial Vehicles (UAVs) are two hot
technologies utilized in cultivation fields, which transform traditional farming practices into a …

Deep Learning (DL) has been described as one of the key subfields of Artificial Intelligence
(AI) that is transforming weed detection for site-specific weed management (SSWM). In the …

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

Despite the perception people may have regarding the agricultural process, the reality is that
today's agriculture industry is data-centered, precise, and smarter than ever. The rapid …

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