54 citations · 111 across the 5 of their papers we have counts for
3 papers · 1 filter
Image segmentation via Cellular Automata
Mark Sandler, Andrey Zhmoginov, Liangcheng Luo +3
In this paper, we propose a new approach for building cellular automata to solve real-world segmentation problems. We design and train a cellular automaton that can successfully se…
Associative Domain Adaptation
Philip Haeusser, Thomas Frerix, Alexander Mordvintsev +1
We propose associative domain adaptation, a novel technique for end-to-end domain adaptation with neural networks, the task of inferring class labels for an unlabeled target domain…
Learning by Association - A versatile semi-supervised training method for neural networks
Philip Häusser, Alexander Mordvintsev, Daniel Cremers
In many real-world scenarios, labeled data for a specific machine learning task is costly to obtain. Semi-supervised training methods make use of abundantly available unlabeled dat…