COMET: A conceptual coupling based metrics suite for software defect prediction. - Diana-Lucia Miholca; Gabriela Czibula; Vlad-Ioan Tomescu (KES, 2020)

A comparative study on using unsupervised learning based data analysis techniques for breast cancer detection. - Stefan Nitica; Gabriela Czibula; Vlad-Ioan Tomescu (SACI, 2020)

FoRConvD: An approach for food recognition on mobile devices using convolutional neural networks and depth maps. - Vlad-Ioan Tomescu (SACI, 2020)

Enhancing the Performance of Image Classification Through Features Automatically Learned from Depth-Maps. - George Ciubotariu; Vlad-Ioan Tomescu; Gabriela Czibula (ICVS, 2021)

A study on using deep autoencoders for imbalanced binary classification. - Vlad-Ioan Tomescu; Gabriela Czibula; Stefan Nitica (KES, 2021)

An in-Depth Analysis of the Software Features' Impact on the Performance of Deep Learning-Based Software Defect Predictors. - Diana-Lucia Miholca; Vlad-Ioan Tomescu; Gabriela Czibula (IEEE Access, 2022)