On Thin Ice: Towards Explainable Conservation Monitoring via Attribution and Perturbations

A recent study highlights the potential of computer vision in enhancing ecological research and conservation monitoring, particularly through the use of explainable models. By applying post-hoc explanations to neural network predictions, researchers aim to build trust and address concerns about the reliability of these technologies in the field. This approach, demonstrated with aerial imagery from Glacier Bay National Park, could significantly improve the monitoring of pinnipeds and other wildlife, making conservation efforts more effective and transparent.