Deep learning constitutes a recent, modern technique for image processing and data
analysis, with promising results and large potential. As deep learning has been successfully …

Plant diseases affect the growth of their respective species, therefore their early identification
is very important. Many Machine Learning (ML) models have been employed for the …

The aim of the proposed work is to review the various AI techniques (fuzzy logic (FL),
artificial neural network (ANN), genetic algorithm (GA), particle swarm optimization (PSO) …

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

Weeds are among the major factors that could harm crop yield. With the advances in
electronic and information technologies, machine vision combined with image processing …

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

Weed detection has become an integral part of precision farming that leverages the IoT
framework. Weeds have become responsible for 45% of the agriculture industry's crop …

Precision farming robots, which target to reduce the amount of herbicides that need to be
brought out in the fields, must have the ability to identify crops and weeds in real time to …

Reducing the use of pesticides through selective spraying is an important component
towards a more sustainable computer-assisted agriculture. Weed identification at early …

Weed management is one of the most important aspects of crop productivity; knowing the
amount and the locations of weeds has been a problem that experts have faced for several …