3 papers
cs.AI2022
Self-Supervised Anomaly Detection by Self-Distillation and Negative Sampling
Nima Rafiee, Rahil Gholamipoorfard, Nikolas Adaloglou +3
Detecting whether examples belong to a given in-distribution or are Out-Of-Distribution (OOD) requires identifying features specific to the in-distribution. In the absence of label…
cs.CV2020
Multi-view adaptive graph convolutions for graph classification
Nikolas Adaloglou, Nicholas Vretos, Petros Daras
In this paper, a novel multi-view methodology for graph-based neural networks is proposed. A systematic and methodological adaptation of the key concepts of classical deep learning…
cs.CV2020
A Comprehensive Study on Deep Learning-based Methods for Sign Language Recognition
Nikolas Adaloglou, Theocharis Chatzis, Ilias Papastratis +7
In this paper, a comparative experimental assessment of computer vision-based methods for sign language recognition is conducted. By implementing the most recent deep neural networ…