11 citations · 19 across the 4 of their papers we have counts for
6 papers · 1 filter
Unsupervised Adversarial Correction of Rigid MR Motion Artifacts
Karim Armanious, Aastha Tanwar, Sherif Abdulatif +3
Motion is one of the main sources for artifacts in magnetic resonance (MR) images. It can have significant consequences on the diagnostic quality of the resultant scans. Previously…
Unsupervised Medical Image Translation Using Cycle-MedGAN
Karim Armanious, Chenming Jiang, Sherif Abdulatif +3
Image-to-image translation is a new field in computer vision with multiple potential applications in the medical domain. However, for supervised image translation frameworks, co-re…
Open-Set Recognition Using Intra-Class Splitting
Patrick Schlachter, Yiwen Liao, Bin Yang
This paper proposes a method to use deep neural networks as end-to-end open-set classifiers. It is based on intra-class data splitting. In open-set recognition, only samples from a…
An Adversarial Super-Resolution Remedy for Radar Design Trade-offs
Karim Armanious, Sherif Abdulatif, Fady Aziz +2
Radar is of vital importance in many fields, such as autonomous driving, safety and surveillance applications. However, it suffers from stringent constraints on its design parametr…
Deep One-Class Classification Using Intra-Class Splitting
Patrick Schlachter, Yiwen Liao, Bin Yang
This paper introduces a generic method which enables to use conventional deep neural networks as end-to-end one-class classifiers. The method is based on splitting given data from…
Active Learning for One-Class Classification Using Two One-Class Classifiers
Patrick Schlachter, Bin Yang
This paper introduces a novel, generic active learning method for one-class classification. Active learning methods play an important role to reduce the efforts of manual labeling…