Semantic Scholar Open Access 2019 198 sitasi

Efficient Pipeline for Camera Trap Image Review

Sara Beery Dan Morris Siyu Yang

Abstrak

Biologists all over the world use camera traps to monitor biodiversity and wildlife population density. The computer vision community has been making strides towards automating the species classification challenge in camera traps, but it has proven difficult to to apply models trained in one region to images collected in different geographic areas. In some cases, accuracy falls off catastrophically in new region, due to both changes in background and the presence of previously-unseen species. We propose a pipeline that takes advantage of a pre-trained general animal detector and a smaller set of labeled images to train a classification model that can efficiently achieve accurate results in a new region.

Topik & Kata Kunci

Penulis (3)

S

Sara Beery

D

Dan Morris

S

Siyu Yang

Format Sitasi

Beery, S., Morris, D., Yang, S. (2019). Efficient Pipeline for Camera Trap Image Review. https://www.semanticscholar.org/paper/775b64705af0d2be8fe5a6fad42a8eef1e3bc6fd

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Informasi Jurnal
Tahun Terbit
2019
Bahasa
en
Total Sitasi
198×
Sumber Database
Semantic Scholar
Akses
Open Access ✓