Search Results for author: Mohamed Yousef

Found 5 papers, 2 papers with code

No Shifted Augmentations (NSA): compact distributions for robust self-supervised Anomaly Detection

no code implementations19 Mar 2022 Mohamed Yousef, Marcel Ackermann, Unmesh Kurup, Tom Bishop

We propose novel architectural modifications to the self-supervised feature learning step, that enable such compact distributions for ID data to be learned.

Out of Distribution (OOD) Detection Self-Supervised Anomaly Detection +2

No Shifted Augmentations (NSA): strong baselines for self-supervised Anomaly Detection

no code implementations29 Sep 2021 Mohamed Yousef, Tom Bishop, Unmesh Kurup

We propose novel architectural modifications to the self-supervised feature learning step, that enable such compact ID distributions to be learned.

Out of Distribution (OOD) Detection Self-Supervised Anomaly Detection +3

Accurate, Data-Efficient, Unconstrained Text Recognition with Convolutional Neural Networks

1 code implementation31 Dec 2018 Mohamed Yousef, Khaled F. Hussain, Usama S. Mohammed

Unconstrained text recognition is an important computer vision task, featuring a wide variety of different sub-tasks, each with its own set of challenges.

Handwriting Recognition License Plate Recognition +1

Cannot find the paper you are looking for? You can Submit a new open access paper.