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Lookup NU author(s): Dr Stephen McGough, Professor Per Berggren
This is the authors' accepted manuscript of a conference proceedings (inc. abstract) published in its final definitive form in 2019. For re-use rights please refer to the publishers terms and conditions.
Methods for cetacean research include photo-identification (photo-id) and passive acoustic monitoring (PAM) which generate thousands of images per expedition that are currently hand categorised by researchers into the individual dolphins sighted. With the vast amount of data obtained it is crucially important to develop a system that is able to categorise this quickly. The Northumberland Dolphin Dataset (NDD) is an on-going novel dataset project made up of above and below water images of, and spectrograms of whistles from, white-beaked dolphins. These are produced by photo-id and PAM data collection methods applied off the coast of Northumberland, UK. This dataset will aid in building cetacean identification models, reducing the number of human-hours required to categorise images. Example use cases and areas identified for speed up are examined.
Author(s): Trotter C, Atkinson G, Sharpe M, McGough AS, Wright N, Berggren P
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: The 6th Workshop on Fine-Grained Visual Categorization Computer Vision and Pattern Recognition (CVPR)
Year of Conference: 2019
Online publication date: 07/08/2022
Acceptance date: 07/08/2019
Date deposited: 03/10/2022
URL: https://doi.org/10.48550/arXiv.1908.02669
DOI: 10.48550/arXiv.1908.02669
