banter is a package for creating hierarchical acoustic event classifiers out of multiple call type detectors.

Automatic dolphin counter

A deep learning image classification project to predict whale and dolphin species

Machine learning project to classify dolphins from drone footage using image and velocity information.

Preliminary analysis of the questionnaire for face-to-face surveys to the targeted fisher groups engaged in gillnet coastal fisheries.

Repos contains code and data that underpins a novel dolphin machine learning model.

This supplementary material contains the files, scripts and methods that were used to develop the analysis of the research article entitled "Risk Assessment of Potential Tourist-Vessel Collision with cetaceans in the Colombian EEZ".

Interactive map of cetacean observations and vessel strike risk in Norwegian and surrounding waters. Conservation screening tool with peer-reviewed collision risk formulas.

Each script and notebook in the repository is well-documented, with extensive logging for transparency and reproducibility. The repository is designed for researchers, data scientists, and conservationists interested in applying data-driven methods to marine ecology and species management.

Six-stage reproducible pipeline for CNN-based passive acoustic monitoring: audio annotation, segmentation, spectrogram generation, image preprocessing, k-fold training, and cross-domain evaluation. Fully configured via YAML.

Open-source interactive globe visualising 25,000+ whale sightings, strandings, acoustic detections and migration routes from 6 species across 5 open scientific databases.