Weed monitoring is the first step in any site‐specific weed management programme. A
relatively large variety of platforms, cameras, sensors and image analysis procedures are …

We propose an instance-based learning approach for segmentation of crop images. The
method proposed is able to automatically discriminate the green textures (crop and weeds) …

This paper proposes a new method, oriented to crop row detection in images from maize
fields with high weed pressure. The vision system is designed to be installed onboard a …

Crop row detection is critical for precision agriculture and automatic navigation. In this paper,
a novel automatic and robust crop row detection method is proposed for maize fields based …

The heavy equipment used at construction sites poses a significant threat to the safety of
surrounding workers due to the inherently poor visibility of the equipment operator. To …

Visual navigation is developing rapidly and is of great significance to improve agricultural
automation. The most important issue involved in visual navigation is extracting a guidance …

This paper proposes an automatic expert system for accuracy crop row detection in maize
fields based on images acquired from a vision system. Different applications in maize …

This paper presents a new automatic and robust crop rows detection algorithm for a vision-
based agricultural machinery guidance system. The algorithm consists of five steps: gray …

This study proposes a new method for detecting curved and straight crop rows in images
captured in maize fields during the initial growth stages of crop and weed plants. The …

An important objective in weed management is the discrimination between grasses
(monocots) and broad-leaved weeds (dicots), because these two weed groups can be …