Aggregating user input in ecology citizen science projects
Camera traps (remote, automatic cameras) are revolutionizing large-scale studies in ecology. The Serengeti Lion Project has used camera traps to produce over 1.5 million pictures of animals in the Serengeti. To analyze these pictures, the Project created Snapshot Serengeti, a citizen science website...
| Main Authors: | , , , |
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| Format: | Conference item |
| Language: | English |
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AAAI Press
2015
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| _version_ | 1811140474480623616 |
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| author | Hines, G Kosmala, M Swanson, A Lintott, C |
| author_facet | Hines, G Kosmala, M Swanson, A Lintott, C |
| author_sort | Hines, G |
| collection | OXFORD |
| description | Camera traps (remote, automatic cameras) are revolutionizing large-scale studies in ecology. The Serengeti Lion Project has used camera traps to produce over 1.5 million pictures of animals in the Serengeti. To analyze these pictures, the Project created Snapshot Serengeti, a citizen science website where volunteers can help classify animals. To increase accuracy, each photo is shown to multiple users and a critical step is aggregating individual classifications. In this paper, we present a new aggregation algorithm which achieves an accuracy of 98.6%, better than many human experts. Our algorithm also requires fewer users per photo than existing methods. The algorithm is intuitive and designed so that nonexperts can understand the end results |
| first_indexed | 2024-03-07T03:21:54Z |
| format | Conference item |
| id | oxford-uuid:b7b47497-aabe-44d6-8006-2779c2da3f1f |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-09-25T04:22:33Z |
| publishDate | 2015 |
| publisher | AAAI Press |
| record_format | dspace |
| spelling | oxford-uuid:b7b47497-aabe-44d6-8006-2779c2da3f1f2024-08-15T09:58:35ZAggregating user input in ecology citizen science projectsConference itemhttp://purl.org/coar/resource_type/c_5794uuid:b7b47497-aabe-44d6-8006-2779c2da3f1fEnglishSymplectic Elements at OxfordAAAI Press2015Hines, GKosmala, MSwanson, ALintott, CCamera traps (remote, automatic cameras) are revolutionizing large-scale studies in ecology. The Serengeti Lion Project has used camera traps to produce over 1.5 million pictures of animals in the Serengeti. To analyze these pictures, the Project created Snapshot Serengeti, a citizen science website where volunteers can help classify animals. To increase accuracy, each photo is shown to multiple users and a critical step is aggregating individual classifications. In this paper, we present a new aggregation algorithm which achieves an accuracy of 98.6%, better than many human experts. Our algorithm also requires fewer users per photo than existing methods. The algorithm is intuitive and designed so that nonexperts can understand the end results |
| spellingShingle | Hines, G Kosmala, M Swanson, A Lintott, C Aggregating user input in ecology citizen science projects |
| title | Aggregating user input in ecology citizen science projects |
| title_full | Aggregating user input in ecology citizen science projects |
| title_fullStr | Aggregating user input in ecology citizen science projects |
| title_full_unstemmed | Aggregating user input in ecology citizen science projects |
| title_short | Aggregating user input in ecology citizen science projects |
| title_sort | aggregating user input in ecology citizen science projects |
| work_keys_str_mv | AT hinesg aggregatinguserinputinecologycitizenscienceprojects AT kosmalam aggregatinguserinputinecologycitizenscienceprojects AT swansona aggregatinguserinputinecologycitizenscienceprojects AT lintottc aggregatinguserinputinecologycitizenscienceprojects |