| Autor: |
Greg Falzon, Christopher Lawson, Ka-Wai Cheung, Karl Vernes, Guy A. Ballard, Peter J. S. Fleming, Alistair S. Glen, Heath Milne, Atalya Mather-Zardain, Paul D. Meek |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
Animals, Vol 10, Iss 1, p 58 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2076-2615 |
| DOI: |
10.3390/ani10010058 |
| Popis: |
We present ClassifyMe a software tool for the automated identification of animal species from camera trap images. ClassifyMe is intended to be used by ecologists both in the field and in the office. Users can download a pre-trained model specific to their location of interest and then upload the images from a camera trap to a laptop or workstation. ClassifyMe will identify animals and other objects (e.g., vehicles) in images, provide a report file with the most likely species detections, and automatically sort the images into sub-folders corresponding to these species categories. False Triggers (no visible object present) will also be filtered and sorted. Importantly, the ClassifyMe software operates on the user’s local machine (own laptop or workstation)—not via internet connection. This allows users access to state-of-the-art camera trap computer vision software in situ, rather than only in the office. The software also incurs minimal cost on the end-user as there is no need for expensive data uploads to cloud services. Furthermore, processing the images locally on the users’ end-device allows them data control and resolves privacy issues surrounding transfer and third-party access to users’ datasets. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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