By combining the proposed feature representation with K-means clustering, we are able to effectively cluster and segment bird calls from multiple species, which ...

A novel model of fuzzy clustering neural network is discussed, which synthesizes unsupervised fuzzy competitive learning algorithm and self-organized ...

This work studies bird sound clustering, the task of deciding for any pair of sound recordings whether the same species of bird can be heard in both, ...

In this work we introduce a technique for feature learning from large volumes of bird sound recordings, inspired by techniques that have proven useful in other ...

Automatic species classification of birds from their sounds has many potential applications in conservation, ecology and archival [11,6]. However, to be useful.

Dec 18, 2023 · This study investigates the utility of feature embeddings extracted from audio classification models to identify bioacoustic classes.

Jun 16, 2023 · We study bird sound clustering, the task of deciding for any pair of sound recordings whether the same species of bird can be heard in both.

In this paper, we investigate acoustic features, visual features, and deep learning for bird sound classification.

May 6, 2023 · Deep learning algorithms can be trained to recognise patterns in bird songs, allowing for accurate and efficient identification of different species.

Nov 14, 2023 · Deep learning-based tools for the detection and classification of vocal species have generated a lot of interest due to their accuracy.