1 code implementation • ICCV 2023 • Declan McIntosh, Alexandra Branzan Albu
From this, we propose Inter-Realization Channels (InReaCh), a fully unsupervised method of detecting and localizing anomalies.
no code implementations • 17 Nov 2022 • Declan McIntosh, Tunai Porto Marques, Alexandra Branzan Albu, Rodney Rountree, Fabio De Leo
Although our system is designed for applications to diverse fish behaviours (i. e, is generic), we demonstrate its application to the detection of sablefish (Anoplopoma fimbria) startle events.
1 code implementation • 8 May 2022 • Declan McIntosh, Tunai Porto Marques, Alexandra Branzan Albu
Based on our results we hypothesize that providing frequency-specific coefficients allows the CNNs to specialize in the identification of structures that are particular to a frequency band, ultimately increasing classification performance, without an increase in computational load.
no code implementations • 28 Nov 2020 • Declan McIntosh, Tunai Porto Marques, Alexandra Branzan Albu, Rodney Rountree, Fabio De Leo
Global warming is predicted to profoundly impact ocean ecosystems.
no code implementations • 1 Jun 2020 • Alireza Rezvanifar, Melissa Cote, Alexandra Branzan Albu
In this paper, we address all of the above issues by leveraging recent advances in DL and adapting an object detection framework based on the You-Only-Look-Once (YOLO) architecture.
1 code implementation • 28 May 2020 • Tunai Porto Marques, Alexandra Branzan Albu
Images captured underwater often suffer from suboptimal illumination settings that can hide important visual features, reducing their quality.
no code implementations • 18 Oct 2019 • Alireza Rezvanifar, Tunai Porto Marques, Melissa Cote, Alexandra Branzan Albu, Alex Slonimer, Thomas Tolhurst, Kaan Ersahin, Todd Mudge, Stephane Gauthier
Tracking the abundance of underwater species is crucial for understanding the effects of climate change on marine ecosystems.