161 citations · 242 across the 7 of their papers we have counts for
9 papers
CatchMonitor: a machine learning system for automated fish discard quantification
Geoff French, Michal Mackiewicz, Mark Fisher +2
We report on the continued development of CatchMonitor, resulting in a prototype computer vision system designed to automatically quantify discarded fish from video footage collect…
Extending Temporal Data Augmentation for Video Action Recognition
Artjoms Gorpincenko, Michal Mackiewicz
Pixel space augmentation has grown in popularity in many Deep Learning areas, due to its effectiveness, simplicity, and low computational cost. Data augmentation for videos, howeve…
Colour augmentation for improved semi-supervised semantic segmentation
Geoff French, Michal Mackiewicz
Consistency regularization describes a class of approaches that have yielded state-of-the-art results for semi-supervised classification. While semi-supervised semantic segmentatio…
Improving Automated Sonar Video Analysis to Notify About Jellyfish Blooms
Artjoms Gorpincenko, Geoffrey French, Peter Knight +2
Human enterprise often suffers from direct negative effects caused by jellyfish blooms. The investigation of a prior jellyfish monitoring system showed that it was unable to reliab…
Virtual Adversarial Training in Feature Space to Improve Unsupervised Video Domain Adaptation
Artjoms Gorpincenko, Geoffrey French, Michal Mackiewicz
Virtual Adversarial Training has recently seen a lot of success in semi-supervised learning, as well as unsupervised Domain Adaptation. However, so far it has been used on input sa…
Using Deep Learning to Count Albatrosses from Space
Ellen Bowler, Peter T. Fretwell, Geoffrey French +1
In this paper we test the use of a deep learning approach to automatically count Wandering Albatrosses in Very High Resolution (VHR) satellite imagery. We use a dataset of manually…
Semi-supervised semantic segmentation needs strong, varied perturbations
Geoff French, Samuli Laine, Timo Aila +2
Consistency regularization describes a class of approaches that have yielded ground breaking results in semi-supervised classification problems. Prior work has established the clus…
Spherical sampling methods for the calculation of metamer mismatch volumes
Michal Mackiewicz, Hans Jakob Rivertz, Graham D. Finlayson
In this paper, we propose two methods of calculating theoretically maximal metamer mismatch volumes. Unlike prior art techniques, our methods do not make any assumptions on the sha…
Self-ensembling for visual domain adaptation
Geoffrey French, Michal Mackiewicz, Mark Fisher
This paper explores the use of self-ensembling for visual domain adaptation problems. Our technique is derived from the mean teacher variant (Tarvainen et al., 2017) of temporal en…