Meet the authors: Georgios Rizos, Jenna L. Lawson, and Björn W. Schuller

Rizos, Georgios; Lawson, Jenna L. ORCID: https://orcid.org/0000-0001-5166-5510; Schuller, Björn W.. 2024 Meet the authors: Georgios Rizos, Jenna L. Lawson, and Björn W. Schuller. Patterns, 5 (3), 100952. 4, pp. 10.1016/j.patter.2024.100952

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Official URL: http://dx.doi.org/10.1016/j.patter.2024.100952

Abstract/Summary

In their recent publication in Patterns, the authors proposed a methodology based on sample-free Bayesian neural networks and label smoothing to improve both predictive and calibration performance on animal call detection. Such approaches have the potential to foster trust in algorithmic decision making and enhance policy making in applications about conservation using recordings made by on-site passive acoustic monitoring equipment. This interview is a companion to these authors’ recent paper, ‘Propagating Variational Model Uncertainty for Bioacoustic Call Label Smoothing’.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1016/j.patter.2024.100952
UKCEH and CEH Sections/Science Areas:	Biodiversity (Science Area 2017-)
ISSN:	2666-3899
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via official URL link.
NORA Subject Terms:	Ecology and Environment
Date made live:	14 Mar 2024 15:08 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/537099

Item Type:

Publication - Article

Digital Object Identifier (DOI):

10.1016/j.patter.2024.100952

UKCEH and CEH Sections/Science Areas:

Biodiversity (Science Area 2017-)

ISSN:

2666-3899

Additional Information. Not used in RCUK Gateway to Research.:

Open Access paper - full text available via official URL link.

NORA Subject Terms:

Ecology and Environment