16 citations · 27 across the 6 of their papers we have counts for
5 papers · 1 filter
Dense FixMatch: a simple semi-supervised learning method for pixel-wise prediction tasks
Miquel Martí i Rabadán, Alessandro Pieropan, Hossein Azizpour +1
We propose Dense FixMatch, a simple method for online semi-supervised learning of dense and structured prediction tasks combining pseudo-labeling and consistency regularization via…
Towards a Unified View of Affinity-Based Knowledge Distillation
Vladimir Li, Atsuto Maki
Knowledge transfer between artificial neural networks has become an important topic in deep learning. Among the open questions are what kind of knowledge needs to be preserved for…
Regularizing CNN Transfer Learning with Randomised Regression
Yang Zhong, Atsuto Maki
This paper is about regularizing deep convolutional networks (CNNs) based on an adaptive framework for transfer learning with limited training data in the target domain. Recent adv…
Target Aware Network Adaptation for Efficient Representation Learning
Yang Zhong, Vladimir Li, Ryuzo Okada +1
This paper presents an automatic network adaptation method that finds a ConvNet structure well-suited to a given target task, e.g., image classification, for efficiency as well as…
A multitask deep learning model for real-time deployment in embedded systems
Miquel Martí, Atsuto Maki
We propose an approach to Multitask Learning (MTL) to make deep learning models faster and lighter for applications in which multiple tasks need to be solved simultaneously, which…