It is a research article published in the journal “Pattern Recognition Letters” in 2016. The document discusses the use of computer vision techniques for automatically classifying flying bird species based on their acoustic events. It describes the methodology used, including the application of Mel-scaled band-pass filters and an AR model to approximate the power spectrum of bird vocalizations. The document also mentions the field recording database used for the study and provides experimental evaluation results and discussions on the performance of the proposed method.
Summary made by Quivr/gpt-3.5-turbo-0613
It is a research article published in the journal “Pattern Recognition Letters” in 2016. The document discusses the use of computer vision techniques for automatically classifying flying bird species based on their acoustic events. It describes the methodology used, including the application of Mel-scaled band-pass filters and an AR model to approximate the power spectrum of bird vocalizations. The document also mentions the field recording database used for the study and provides experimental evaluation results and discussions on the performance of the proposed method.