Acoustic individual identification in a species of field cricket using deep learning

Kabuga, EORCID logo; Nandi, DORCID logo; Burrell, SORCID logo; Dlamini, G; Balakrishnan, R; Bah, BORCID logo and Durbach, IORCID logo (2026). Acoustic individual identification in a species of field cricket using deep learning. [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.20542967
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This Zenodo archive preserves the source code and a representative subset of the data accompanying the paper: "Acoustic individual identification in a species of field cricket using deep learning." The repository contains all scripts required for data preprocessing, feature extraction, model development, training, evaluation, and reproduction of the computational workflow described in the publication. To facilitate testing and reproducibility while maintaining a manageable Github archive size, only a representative subset of the dataset is included in this repository. This subset is sufficient to verify the installation, execute the analysis pipeline, and reproduce example experiments. The complete dataset used in the study is archived separately and distributed through a dedicated Zenodo record: Full Dataset: DOI: 10.5281/zenodo.20596912. Researchers wishing to reproduce the full experimental results reported in the publication should download the complete dataset from the dataset archive and follow the instructions provided in the repository documentation.

Keywords

passive monitoring; deep learning; convolutional neural networks; acoustic individual identification; acoustic signatures; Machine learning

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