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Bumblebee Re-Identification Dataset [in press]

Tausch, Frederic; Stock, Simon; Fricke, Julian; Klein, Olaf

Abstract (englisch):
Over the past decade, entomologists have observed a worldwide decline in the population of pollinating insects. Even though there is a number of hypotheses about of potential underlying causes for this decline, there are concerns that insecticides are at least partially responsible. The design of insecticides requires accurate risk assessment procedures to avoid damage to beneficial insects and like pollinators such as the buff-tailed bumblebee (Bombus terrestris). Therefore, current guideline drafts by the EFSA include homing fight studies to test insect behavioral performance. Since these studies (eg, homing study) inspect the individual's change in behavior, insect re-ID (reidentification) is crucial. Current bumblebee re-ID techniques are limited to placing markers on individual subjects, which can be analog or digital (RFID). These steps are very time consuming, intrusive and are prone to mechanical failure. To find a solution to remedy these shortcomings, a visual approach is proposed. Therefore we propose the following bumblebee re-ID dataset in order to build such systems.

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Zugehörige Institution(en) am KIT Institut für Technik der Informationsverarbeitung (ITIV)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2020
Sprache Englisch
Identifikator KITopen-ID: 1000117602
Erschienen in Proceedings of the IEEE Winter Conference on Applications of Computer Vision Workshops
Veranstaltung IEEE Winter Conference on Applications of Computer Vision (WACV 2020), Snowmass Village, CO, USA, 01.03.2020 – 05.03.2020
Verlag IEEE
Seiten 35-37
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