The alarming decline in global biodiversity, driven by various factors, underscores the urgent
need for large-scale wildlife monitoring. In response, scientists have turned to automated …

Class imbalance is one of the major issues for the application of deep learning for remote
sensing imagery. High-resolution remote sensing image sample sets are prone to cause the …

Identifying and classifying objects in aerial images are two significant and complex issues in
computer vision. The fine-grained classification of objects in overhead images has become …

The integration of Artificial Intelligence (AI) into biodiversity research and conservation is
growing rapidly, demonstrating great potential in reducing the intensive human labor …

We explore the challenges of human-in-the-loop frameworks to label wildlife recognition
datasets with a neural network. In wildlife imagery, the main challenges for a model to assist …

Automatically detecting sound events with Artificial Intelligence (AI) has become increasingly
popular in the field of bioacoustics, particularly for wildlife monitoring and conservation …

Résumé L'utilisation du drone dans le domaine de l'expertise écologique, et notamment en
biologie de la conservation a pris son essor au début des années 2010 et s' inscrit …