A deep active learning system for species identification and counting in camera trap images
A deep active learning system for species identification and counting in camera trap images
Abstract A typical camera trap survey may produce millions of images that require slow, expensive manual review. Consequently, critical conservation questions may be answered too slowly to support decisionāmaking. Recent studies demonstrated the potential for computer vision to dramatically increase efficiency in imageābased biodiversity surveys; however, the literature has focused ā¦