Economical crowdsourcing for camera trap image classification
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Summary
The species‐specific nature of the findings suggests that the performance of crowdsourcing projects is likely to be highly sensitive to the local fauna and context, and the generality of consensus algorithms will be an important consideration for ecologists interested in harnessing the power of the crowd to assist with camera trapping studies.
- Type
- article
- Published
- 2018-07-04
- Cited by
- 52
- References
- 56
- Access
- Open access
- OpenAlex
- https://openalex.org/W2800825998
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:64489102
Keywords
Crowdsourcing, Citizen science, Context (archaeology), Scale (ratio), Data science
References
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- Dates and Times Made Easy with lubridate
Cited by
- Wild boar in focus: initial model outputs of wild boar distribution based on occurrence data and identification of priority areas for data collection
- Monitoring the UK’s wild mammals: A new grammar for citizen science engagement and ecology
- Wildlife surveillance using deep learning methods
- Adopting Citizen Science as a Tool to Enhance Monitoring for an Environment Agency
- Innovations in Camera Trapping Technology and Approaches: The Integration of Citizen Science and Artificial Intelligence
- Bayesian item response models for citizen science ecological data
- Application of the Random Encounter Model in citizen science projects to monitor animal densities
- Insights from unseen individuals – using non-invasive approaches to study population biology of white-tailed deer in Finland
- A review of factors to consider when using camera traps to study animal behavior to inform wildlife ecology and conservation
- Searching for rare and secretive snakes: are camera-trap and box-trap methods interchangeable?
- This is my project! The influence of involvement on psychological ownership and wildlife conservation
- Chimpanzee identification and social network construction through an online citizen science platform
- Use of a novel camera trapping approach to measure small mammal responses to peatland restoration
- Remote sensing of mining and haulage equipment arrangement in Russia: A case-study of the coal and iron ore industry
- The Verification of Ecological Citizen Science Data: Current Approaches and Future Possibilities
- Understanding the reliability of citizen science observational data using item response models
- Citizen science decisions: A Bayesian approach optimises effort
- Citizen Science Data Collection for Integrated Wildlife Population Analyses
- The Partnership of Citizen Science and Machine Learning: Benefits, Risks, and Future Challenges for Engagement, Data Collection, and Data Quality
- Arboreal camera trapping: a reliable tool to monitor plant‐frugivore interactions in the trees on large scales
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