A machine learning framework to classify Southeast Asian echolocating bats

• Main Authors: Natalie, Yoh, Tigga, Kingston, Ellen, McArthur, Aylen, Oliver E., Huang, Joe Chun-Chia, Emy Ritta, Jinggong, Faisal Ali, Anwarali Khan, Lee, Benjamin P.Y.H, Mitchell, Simon L., Bicknell, Jake E.
• Format: Article
• Language: English
• Published: Elsevier Science, Ltd. 2022
• Subjects: QL Zoology
• Online Access: http://ir.unimas.my/id/eprint/38037/1/A%20machine%20learning%20framework.pdf; http://ir.unimas.my/id/eprint/38037/; https://www.sciencedirect.com/science/article/pii/S1470160X22001674#!
• Institution: Universiti Malaysia Sarawak

Bats comprise a quarter of all mammal species, provide key ecosystem services and serve as effective bioindicators. Automated methods for classifying echolocation calls of free-flying bats are useful for monitoring but are not widely used in the tropics. This is particularly problematic in Southeas...