Adaptive representations of sound for automatic insect recognition.

ABSTRACT: Insect population numbers and biodiversity have been rapidly declining with time, and monitoring these trends has become increasingly important for conservation measures to be effectively implemented. But monitoring methods are often invasive, time and resource intense, and prone to various biases. Many insect species produce characteristic sounds that can easily be detected and recorded without large cost or effort. Using deep learning methods, insect sounds from field recordings could be automatically detected and classified to monitor biodiversity and species distribution ranges. We implement this using recently published datasets of insect sounds (up to 66 species of Orthoptera and Cicadidae) and machine learning methods and evaluate their potential for acoustic insect monitoring. We c

SUBMITTER: Faiß M 

PROVIDER: S-EPMC10578591 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature