Unsupervised Representation Learning by Discovering Reliable Image Relations

no code implementations • 18 Nov 2019 • Timo Milbich, Omair Ghori, Ferran Diego, Björn Ommer

To nevertheless find those relations which can be reliably utilized for learning, we follow a divide-and-conquer strategy: We find reliable similarities by extracting compact groups of images and reliable dissimilarities by partitioning these groups into subsets, converting the complicated overall problem into few reliable local subproblems.

Representation Learning Transfer Learning

CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation

no code implementations • 23 Oct 2018 • Radek Mackowiak, Philip Lenz, Omair Ghori, Ferran Diego, Oliver Lange, Carsten Rother

State of the art methods for semantic image segmentation are trained in a supervised fashion using a large corpus of fully labeled training images.

Active Learning Image Segmentation +2