arXiv AI By Paul Fergus, Philip Stephens, Russell A. Hill, Lee Oliver, Katie Appleby, Sarah Beatham, Naomi Davies Walsh, Stuart Nixon, Naomi Matthews, Chris Sutherland, Kelly Hitchcock

Democratising Camera Trap AI: An Open-Source Model for Detecting UK Mammals

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arXiv:2606. 10940v1 Announce Type: cross Abstract: Camera traps have become a cornerstone of biodiversity monitoring, but the artificial intelligence that turns vast quantities of images into usable ecological data is often locked behind commercial platforms or trained on fauna that does not match that of the British Isles.

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Democratising Camera Trap AI: An Open-Source Model for Detecting UK Mammals

Camera traps have become a cornerstone of biodiversity monitoring, but the artificial intelligence that turns vast quantities of images into usable ecological data is often locked behind commercial platforms or trained on fauna that does not match that of the British Isles. In an attempt to remove barriers and increase uptake, we release an open-source object detection model for 31 classes, 28 common UK mammal and bird species, plus utility classes for humans, calibration poles, and vehicles, drawn from a curated dataset of 48,165 labelled instances assembled from multiple sites over a decade of operational deployment through Conservation AI and its successor, Trap Tracker.