Automatic Bird Species Recognition using Audio and Image Data: A Short Review

Studies related to bird species identification, movements, and behavior are important for protecting the environment and measuring biodiversity, especially for ornithological research and conservation. Researchers have conducted extensive research on automated bird recognition using images, videos, and audio recordings for biological studies, environmental monitoring, and bird detection and localization. Various approaches have been developed using machine learning, computer vision, and deep learning models. This review examines the current state of automatic bird recognition methods, including sources of data, models, and performance, as well as their limitations, research gaps, and future directions.