Search Results for author:
Found 11 papers, 3 papers with code
Self-ensembling for visual domain adaptation
This paper explores the use of self-ensembling for visual domain adaptation problems.
Ranked #1 on
Domain Adaptation
on Synth Signs-to-GTSRB
Spherical sampling methods for the calculation of metamer mismatch volumes
In this paper, we propose two methods of calculating theoretically maximal metamer mismatch volumes.
Semi-supervised semantic segmentation needs strong, varied perturbations
We analyze the problem of semantic segmentation and find that its' distribution does not exhibit low density regions separating classes and offer this as an explanation for why semi-supervised segmentation is a challenging problem, with only a few reports of success.
Using Deep Learning to Count Albatrosses from Space
In this paper we test the use of a deep learning approach to automatically count Wandering Albatrosses in Very High Resolution (VHR) satellite imagery.
Semi-supervised semantic segmentation needs strong, high-dimensional perturbations
Consistency regularization describes a class of approaches that have yielded ground breaking results in semi-supervised classification problems.
Virtual Adversarial Training in Feature Space to Improve Unsupervised Video Domain Adaptation
Virtual Adversarial Training has recently seen a lot of success in semi-supervised learning, as well as unsupervised Domain Adaptation.
Improving Automated Sonar Video Analysis to Notify About Jellyfish Blooms
Human enterprise often suffers from direct negative effects caused by jellyfish blooms.
Colour augmentation for improved semi-supervised semantic segmentation
Consistency regularization describes a class of approaches that have yielded state-of-the-art results for semi-supervised classification.
SUB-Depth: Self-distillation and Uncertainty Boosting Self-supervised Monocular Depth Estimation
Depth models trained with SUB-Depth outperform the same models trained in a standard single-task SDE framework.
Extending Temporal Data Augmentation for Video Action Recognition
Pixel space augmentation has grown in popularity in many Deep Learning areas, due to its effectiveness, simplicity, and low computational cost.
Computer Vision Pipeline for Automated Antarctic Krill Analysis
British Antarctic Survey (BAS) researchers launch annual expeditions to the Antarctic in order to estimate Antarctic Krill biomass and assess the change from previous years.
