Exploring deep learning techniques for wild animal behaviour classification using animal‐borne accelerometers

Exploring deep learning techniques for wild animal behaviour classification using animal‐borne accelerometers

Abstract Machine learning‐based behaviour classification using acceleration data is a powerful tool in bio‐logging research. Deep learning architectures such as convolutional neural networks (CNN), long short‐term memory (LSTM) and self‐attention mechanism as well as related training techniques have...

Full description

Bibliographic Details
Main Authors: Ryoma Otsuka, Naoya Yoshimura, Kei Tanigaki, Shiho Koyama, Yuichi Mizutani, Ken Yoda, Takuya Maekawa
Format: Article
Language:English
Published: Wiley 2024-04-01
Series:Methods in Ecology and Evolution
Subjects:
acceleration sensor
animal behaviour classification
bio‐logging
data augmentation
deep learning
machine learning
Online Access:https://doi.org/10.1111/2041-210X.14294

Internet

https://doi.org/10.1111/2041-210X.14294

Similar Items