6 citations · 20 across the 17 of their papers we have counts for
46 papers
Discriminability-enforcing loss to improve representation learning
Florinel-Alin Croitoru, Diana-Nicoleta Grigore, Radu Tudor Ionescu
During the training process, deep neural networks implicitly learn to represent the input data samples through a hierarchy of features, where the size of the hierarchy is determine…
A realistic approach to generate masked faces applied on two novel masked face recognition data sets
Tudor Mare, Georgian Duta, Mariana-Iuliana Georgescu +4
The COVID-19 pandemic raises the problem of adapting face recognition systems to the new reality, where people may wear surgical masks to cover their noses and mouths. Traditional…
Contextual Convolutional Neural Networks
Ionut Cosmin Duta, Mariana Iuliana Georgescu, Radu Tudor Ionescu
We propose contextual convolution (CoConv) for visual recognition. CoConv is a direct replacement of the standard convolution, which is the core component of convolutional neural n…
Improving the Authentication with Built-in Camera Protocol Using Built-in Motion Sensors: A Deep Learning Solution
Cezara Benegui, Radu Tudor Ionescu
We propose an enhanced version of the Authentication with Built-in Camera (ABC) protocol by employing a deep learning solution based on built-in motion sensors. The standard ABC pr…
SaRoCo: Detecting Satire in a Novel Romanian Corpus of News Articles
Ana-Cristina Rogoz, Mihaela Gaman, Radu Tudor Ionescu
In this work, we introduce a corpus for satire detection in Romanian news. We gathered 55,608 public news articles from multiple real and satirical news sources, composing one of t…
FreSaDa: A French Satire Data Set for Cross-Domain Satire Detection
Radu Tudor Ionescu, Adrian Gabriel Chifu
In this paper, we introduce FreSaDa, a French Satire Data Set, which is composed of 11,570 articles from the news domain. In order to avoid reporting unreasonably high accuracy rat…