| dc.citation.ctitle | Plant Health Research and Extension Experiences for Undergraduates Poster Symposium, Summer 2022 | |
| dc.contributor.author | Dykstra, Murphy | |
| dc.contributor.author | Spiesman, Brian | |
| dc.date.accessioned | 2026-10-28T21:55:00Z | |
| dc.date.issued | 2026-07-30 | |
| dc.description.abstract | Objectives: Our study investigates the success of a new method of pollinator identification using computer vision to analyze images of bees in torpor. If successful, this technology will be useful to researchers, land managers, and bee enthusiasts, making bee identification more accessible, while requiring less bees to be killed for research purposes. This project will provide preliminary results for potential future, larger scale projects in the Spiesman lab. | |
| dc.description.conference | Plant Health Research and Extension Experiences for Undergraduates Poster Symposium, Summer 2025 | |
| dc.description.sponsorship | This work is supported by the NIFA Research and Extension Experiences for Undergraduates (REEU) Program grant no. 2024-68018-42431/project accession no. 1032359 from the U.S. Department of Agriculture, National Institute of Food and Agriculture. | |
| dc.identifier.uri | https://hdl.handle.net/2097/47485 | |
| dc.language.iso | en_US | |
| dc.rights | � Author(s). This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). | |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | |
| dc.subject | pollinators | |
| dc.subject | induced torpor | |
| dc.subject | imaging | |
| dc.subject | computer vision | |
| dc.subject | entomology | |
| dc.subject | USDA NIFA 2024-68018-42431 | |
| dc.title | Bee Identification Using Computer Vision and Images of Induced Torpor | |
| dc.type | Text |
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