Iterative Human and Automated Identification of Wildlife Images

Understand

Camera trapping is increasingly used to monitor wildlife, but this technology typically requires extensive data annotation.

• Recently, deep learning has significantly advanced automatic wildlife recognition.
• However, current methods are hampered by a dependence on large static data sets when wildlife data is intrinsically dynamic and involves long-tailed distributions.
• These two drawbacks can be overcome through a hybrid combination of machine learning and humans in the loop.