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 …

A key goal of contemporary agriculture is to dramatically increase production of food, feed,
fiber, and biofuel products in a sustainable fashion, facing the pressure of diminishing farm …

In recent years, weeds have been responsible for most agricultural yield losses. To deal with
this threat, farmers resort to spraying the fields uniformly with herbicides. This method not …

Unmanned aerial vehicles (UAVs) and other robots in smart farming applications offer the
potential to monitor farm land on a per-plant basis, which in turn can reduce the amount of …

Weeds have a significant impact on sesame throughout its early stages of development, thus
they must be rigorously controlled. However, the shape of sesame seedlings and weeds are …

The current crop rows detection based on machine vision generally has the problems of low
detection accuracy and poor real-time performance. Moreover, crop rows detection remains …

Accurate extraction of navigation path is very important for automated navigation of
agricultural robots. Based on the machine vision system, this paper proposes a new …

Nowadays, the development of robots and smart tractors for the automation of sowing,
harvesting, weeding etc. is transforming agriculture. Farmers are moving from an agriculture …

This article proposes a novel method for detecting forest fires, through the use of a new color
index, called the Forest Fire Detection Index (FFDI), developed by the authors. The index is …

Knowing before harvesting how many plants have emerged and how they are growing is
key in optimizing labour and efficient use of resources. Unmanned aerial vehicles (UAV) are …