Reliably Decoding Autoencoders´Latent Spaces for One-Class-Learning Image Inspection Scenarios

Research output: Chapter in Book or Conference Proceedings › Conference Proceedings with Oral Presentation › peer-review

Original language	English
Title of host publication	Proceedings of the OAGM Workshop 2018, Medical Image Analysis
Pages	90-93
Number of pages	4
Publication status	Published - 2018
Event	OEAGM Workshop 2018 - Duration: 15 May 2018 → 16 May 2018

Conference	OEAGM Workshop 2018
Period	15/05/18 → 16/05/18

Research Field

@inproceedings{7916ba481fc84905bed1ca01c802c0a8,

title = "Reliably Decoding Autoencoders´Latent Spaces for One-Class-Learning Image Inspection Scenarios",

author = "Daniel Soukup and Thomas Pinetz",

year = "2018",

language = "English",

isbn = "978-3-85125-603-1",

pages = "90--93",

booktitle = "Proceedings of the OAGM Workshop 2018, Medical Image Analysis",

note = "OEAGM Workshop 2018 ; Conference date: 15-05-2018 Through 16-05-2018",

}

TY - GEN

T1 - Reliably Decoding Autoencoders´Latent Spaces for One-Class-Learning Image Inspection Scenarios

AU - Pinetz, Thomas

A2 - Soukup, Daniel

PY - 2018

Y1 - 2018

M3 - Conference Proceedings with Oral Presentation

SN - 978-3-85125-603-1

SP - 90

EP - 93

BT - Proceedings of the OAGM Workshop 2018, Medical Image Analysis

T2 - OEAGM Workshop 2018

Y2 - 15 May 2018 through 16 May 2018

ER -