Mining Self-similarity: Label Super-Resolution with Epitomic Representations

Autor:	Caleb Robinson, Nebojsa Jojic, Anthony Ortiz, Kolya Malkin
Rok vydání:	2020
Předmět:	Current (mathematics) Self-similarity business.industry Simple (abstract algebra) Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Segmentation Artificial intelligence State (computer science) business Convolutional neural network Image (mathematics)
Zdroj:	Computer Vision – ECCV 2020 ISBN: 9783030585730 ECCV (26)
Popis:	We show that simple patch-based models, such as epitomes (Jojic et al., 2003), can have superior performance to the current state of the art in semantic segmentation and label super-resolution, which uses deep convolutional neural networks. We derive a new training algorithm for epitomes which allows, for the first time, learning from very large data sets and derive a label super-resolution algorithm as a statistical inference over epitomic representations. We illustrate our methods on land cover mapping and medical image analysis tasks.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::81a3a431f14ba49bd834516cc93f1304 https://doi.org/10.1007/978-3-030-58574-7_32 Zobrazit plný text záznamu