Automated location invariant animal detection in camera trap images using publicly available data sources.

ABSTRACT: A time-consuming challenge faced by camera trap practitioners is the extraction of meaningful data from images to inform ecological management. An increasingly popular solution is automated image classification software. However, most solutions are not sufficiently robust to be deployed on a large scale due to lack of location invariance when transferring models between sites. This prevents optimal use of ecological data resulting in significant expenditure of time and resources to annotate and retrain deep learning models.We present a method ecologists can use to develop optimized location invariant camera trap object detectors by (a) evaluating publicly available image datasets characterized by high intradataset variability in training deep learning models for camera trap object detectio

SUBMITTER: Shepley A 

PROVIDER: S-EPMC8093655 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature