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Author Steen, Kim Arild ♦ Therkildsen, Ole Roland ♦ Green, Ole ♦ Karstoft, Henrik
Source World Health Organization (WHO)-Global Index Medicus
Content type Text
Publisher Multidisciplinary Digital Publishing Institute
File Format HTM / HTML
Language English
Difficulty Level Medium
Subject Domain (in DDC) Natural sciences & mathematics ♦ Life sciences; biology ♦ Natural history of organisms ♦ Technology ♦ Medicine & health ♦ Agriculture & related technologies
Subject Domain (in MeSH) Eukaryota ♦ Organisms ♦ Technology, Industry, and Agriculture ♦ Technology and Food and Beverages
Subject Keyword Discipline Biotechnology ♦ Agriculture ♦ Weed Control ♦ Methods ♦ Animals ♦ Birds ♦ Physiology ♦ Female ♦ Humans ♦ Journal Article ♦ Research Support, Non-u.s. Gov't
Abstract Mechanical weeding is an important tool in organic farming. However, the use of mechanical weeding in conventional agriculture is increasing, due to public demands to lower the use of pesticides and an increased number of pesticide-resistant weeds. Ground nesting birds are highly susceptible to farming operations, like mechanical weeding, which may destroy the nests and reduce the survival of chicks and incubating females. This problem has limited focus within agricultural engineering. However, when the number of machines increases, destruction of nests will have an impact on various species. It is therefore necessary to explore and develop new technology in order to avoid these negative ethical consequences. This paper presents a vision-based approach to automated ground nest detection. The algorithm is based on the fusion of visual saliency, which mimics human attention, and incremental background modeling, which enables foreground detection with moving cameras. The algorithm achieves a good detection rate, as it detects 28 of 30 nests at an average distance of 3.8 m, with a true positive rate of 0.75.
Description Country affiliation: Denmark
Author Affiliation: Steen KA ( Department of Engineering, Aarhus University, Finlandsgade 22, 8200 Aarhus N, Denmark.; Therkildsen OR ( Department of Bioscience, Aarhus University, Grenåvej 14, 8410 Rønde, Denmark.; Green O ( Kongskilde Industries, Strategic Development, Niels Pedersens Allé 2, 8830 Tjele, Denmark.; Karstoft H ( Department of Engineering, Aarhus University, Finlandsgade 22, 8200 Aarhus N, Denmark.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Reading ♦ Research ♦ Self Learning
Interactivity Type Expositive
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2015-03-02
Publisher Place Switzerland
e-ISSN 14248220
Journal Sensors
Volume Number 15
Issue Number 3

Source: WHO-Global Index Medicus