Citizen Science and Machine Learning for Research and Nature Conservation: The Case of Eurasian Lynx, Free-ranging Rodents and Insects
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arXiv
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| Main Authors: | , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866916146754617344 |
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| author | Skorupska, Kinga Stryjek, Rafał Wierzbowska, Izabela Bebas, Piotr Grzeszczuk, Maciej Gago, Piotr Kowalski, Jarosław Krzywicki, Maciej Lazarek, Jagoda Kopeć, Wiesław |
| author_facet | Skorupska, Kinga Stryjek, Rafał Wierzbowska, Izabela Bebas, Piotr Grzeszczuk, Maciej Gago, Piotr Kowalski, Jarosław Krzywicki, Maciej Lazarek, Jagoda Kopeć, Wiesław |
| contents | Technology is increasingly used in Nature Reserves and National Parks around the world to support conservation efforts. Endangered species, such as the Eurasian Lynx (Lynx lynx), are monitored by a network of automatic photo traps. Yet, this method produces vast amounts of data, which needs to be prepared, analyzed and interpreted. Therefore, researchers working in this area increasingly need support to process this incoming information. One opportunity is to seek support from volunteer Citizen Scientists who can help label the data, however, it is challenging to retain their interest. Another way is to automate the process with image recognition using convolutional neural networks. During the panel, we will discuss considerations related to nature research and conservation as well as opportunities for the use of Citizen Science and Machine Learning to expedite the process of data preparation, labelling and analysis. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_02906 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Citizen Science and Machine Learning for Research and Nature Conservation: The Case of Eurasian Lynx, Free-ranging Rodents and Insects Skorupska, Kinga Stryjek, Rafał Wierzbowska, Izabela Bebas, Piotr Grzeszczuk, Maciej Gago, Piotr Kowalski, Jarosław Krzywicki, Maciej Lazarek, Jagoda Kopeć, Wiesław Human-Computer Interaction Computer Vision and Pattern Recognition Computers and Society Machine Learning Technology is increasingly used in Nature Reserves and National Parks around the world to support conservation efforts. Endangered species, such as the Eurasian Lynx (Lynx lynx), are monitored by a network of automatic photo traps. Yet, this method produces vast amounts of data, which needs to be prepared, analyzed and interpreted. Therefore, researchers working in this area increasingly need support to process this incoming information. One opportunity is to seek support from volunteer Citizen Scientists who can help label the data, however, it is challenging to retain their interest. Another way is to automate the process with image recognition using convolutional neural networks. During the panel, we will discuss considerations related to nature research and conservation as well as opportunities for the use of Citizen Science and Machine Learning to expedite the process of data preparation, labelling and analysis. |
| title | Citizen Science and Machine Learning for Research and Nature Conservation: The Case of Eurasian Lynx, Free-ranging Rodents and Insects |
| topic | Human-Computer Interaction Computer Vision and Pattern Recognition Computers and Society Machine Learning |
| url | https://arxiv.org/abs/2403.02906 |