The Effects of Signal-to-Noise Ratio on Generative Adversarial Networks Applied to Marine Bioacoustic Data

no code implementations • 22 Dec 2023 • Georgia Atkinson, Nick Wright, A. Stephen McGough, Per Berggren

In recent years generative adversarial networks (GANs) have been used to supplement datasets within the field of marine bioacoustics.

Towards Automatic Cetacean Photo-Identification: A Framework for Fine-Grain, Few-Shot Learning in Marine Ecology

no code implementations • 7 Dec 2022 • Cameron Trotter, Nick Wright, A. Stephen McGough, Matt Sharpe, Barbara Cheney, Mònica Arso Civil, Reny Tyson Moore, Jason Allen, Per Berggren

Photo-identification (photo-id) is one of the main non-invasive capture-recapture methods utilised by marine researchers for monitoring cetacean (dolphin, whale, and porpoise) populations.

Few-Shot Learning

NDD20: A large-scale few-shot dolphin dataset for coarse and fine-grained categorisation

no code implementations • 27 May 2020 • Cameron Trotter, Georgia Atkinson, Matt Sharpe, Kirsten Richardson, A. Stephen McGough, Nick Wright, Ben Burville, Per Berggren

We introduce the Northumberland Dolphin Dataset 2020 (NDD20), a challenging image dataset annotated for both coarse and fine-grained instance segmentation and categorisation.

Instance Segmentation Segmentation +1

The Northumberland Dolphin Dataset: A Multimedia Individual Cetacean Dataset for Fine-Grained Categorisation

no code implementations • 7 Aug 2019 • Cameron Trotter, Georgia Atkinson, Matthew Sharpe, A. Stephen McGough, Nick Wright, Per Berggren

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.