Agriculture is considered one of the most important sectors that play a strategic role in
ensuring food security. However, with the increasing world's population, agri-food demands …

In the modern era, deep learning techniques have emerged as powerful tools in image
recognition. Convolutional Neural Networks, one of the deep learning tools, have attained …

This paper presents a comprehensive review of emerging technologies for the internet of
things (IoT)-based smart agriculture. We begin by summarizing the existing surveys and …

The demand for intelligent agriculture is increasing due to the continuous impact of world
food and environmental crises. Focusing on fruit detection, with the rapid development of …

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 …

The utilization of machine vision and its associated algorithms improves the efficiency,
functionality, intelligence, and remote interactivity of harvesting robots in complex …

Computer vision technologies have attracted significant interest in precision agriculture in
recent years. At the core of robotics and artificial intelligence, computer vision enables …

Real-time detection of apples in orchards is one of the most important methods for judging
growth stages of apples and estimating yield. The size, colour, cluster density, and other …

There is a rapid increase in the adoption of emerging technologies like the Internet of Things
(IoT), Unmanned Aerial Vehicles (UAV), Internet of Underground Things (IoUT), Data …