Published November 5, 2025
| Version v1
Dataset
Open
Arctic diel and circadian acoustic pattern of Orcas, Fin, and Humpback whales revealed by deep learning from two months of continuous recordings, supporting data
Authors/Creators
-
1.
University of Pavia
- 2. Centre International d'Intelligence Artificielle en Acoustique Naturelle (CIAN) https://cian.lis-lab.fr, Toulon France
- 3. Université de Toulon, Aix Marseille Univ, CNRS, DYNI, LIS, Toulon France
Contributors
Data collector:
- 1. Centre International d'Intelligence Artificielle en Acoustique Naturelle (CIAN) https://cian.lis-lab.fr, Toulon France
- 2. Université de Toulon, Aix Marseille Univ, CNRS, LIS, Marseille, France
- 3. Valhalla expeditions
- 4. Longitude 181
- 5. Université de Toulon, Aix Marseille Univ, CNRS, DYNI, LIS, Toulon France
Description
This dataset is a sample of the YOLO detection made in Seglvik that supported the findings published in the journal article:
"Arctic diel and circadian acoustic pattern of Orcas, Fin, and Humpback whales revealed by deep learning from two months of continuous recordings".
The species_detection_sample.csv is a sample of the detection data information on which presence and detection rate measurments were based.
A soundfile is provided for each detection. To find the detections corresponding to specific sound files, one should select on the voc_ID column.
The file .ipynb is the code used to generate the figures and perform statistical analyzes.
Files
datasets.zip
Files
(17.8 GB)
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md5:80d16fa4f557899109f8d63f98161a85
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md5:2343c2eb0b90ee0839260397922c60b4
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md5:05e8e09e4f6d8a75a0c2d06b109ebe7c
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