International Journal of Neural Systems Authors Enol García González, Mădălina Dicu, José R. Villar, Camelia Chira Abstract The automatic detection of anomalies in medical images is a significant challenge in the assisted diagnosis of neurodegenerative diseases such as Alzheimer’s. This paper presents an anomaly detection model based on Transformers for the analysis of brain…
Hybrid Artificial Intelligence Systems Authors D. Trandafir, Mădălina Dicu, Camelia Chira Abstract Breast cancer remains a major cause of cancer-related mortality among women worldwide, making accurate lesion detection essential for improving survival rates and supporting clinical diagnosis. Although current pretrained models for predicting benign or malignant lesions achieve high accuracy, they often focus on…
Frontiers in Artificial Intelligence Authors Dan-Cristian George, Mihai-Alexandru Hulubeac, Ştefan-Lucian Grămadă, Z. Bálint, L. Dioşan Abstract Cardiac arrhythmias often progress without clear symptoms and may remain undetected until severe complications occur. Continuous monitoring through consumer smartwatches offers a scalable and non-invasive opportunity for real-time rhythm screening in free-living conditions. However, wrist-based photoplethysmography (PPG) signals…
European Archives of Oto-Rhino-Laryngology Authors I. Pușcaș, Anda Gâta, P. Rizzo, M. Stellin, V. Rampinelli, D. Tomasini, C. Piazza, Daniele Borsetto, W. Ince, C. Chiesa-Estomba, Maria Landa-Garmendia, P. Surda, Eleanor J. Crossley, Matt Lechner, Teodora Maria Ursu, L. Cernau, Adél Bajcsi, Laura-Silvia Dioşan, C. Chira, Alexandra Roman, V. Gâta, Alexandru Irimie, Silviu Albu Abstract…
International Conference on Computer Supported Education Authors L. Cernau, L. Diosan, Camelia Serban Abstract This study offers preliminary insights into the adoption of Generative Artificial Intelligence (GenAI) tools in computer science (CS) education, drawing on responses from 202 university-level computer science students, 16 educators, and 6 industry professionals. Employing a three-dimensional approach, the study…
Hybrid Artificial Intelligence Systems Authors Anikó Kopacz, Enol García González, Camelia Chira, José R. Villar Abstract Multi-robot path planning is essential for industrial operations, e.g., for manufacturing and warehouse logistics. Traditional path planning approaches may impose an unnecessary increase in computational demands when countered by unexpected events or failures. Thus, investigating machine learning approaches,…
Proceedings of the 18th International Conference on Agents and Artificial Intelligence Authors L. Cernau, A. Dobrescu, Ecaterina Cărbune, Georgiana Asandei Abstract The use of large language models (LLMs) to analyse and identify errors in code is becoming increasingly common among developers. While many studies aim to improve the quality and effectiveness of LLM-generated code,…
Proceedings of the 18th International Conference on Agents and Artificial Intelligence Authors Anikó Kopacz, Camelia Chira Abstract Influence maximization is a network optimization problem, which consists of selecting nodes as sources while maximizing the spread of information. The source nodes that are initially activated form the seed set. Polarity-related influence maximization accounts for having…
arXiv.org Authors Alexandru Manole, Laura Diosan Abstract Most information in our world is organized hierarchically; however, many Deep Learning approaches do not leverage this semantically rich structure. Research suggests that human learning benefits from exploiting the hierarchical structure of information, and intelligent models could similarly take advantage of this through multi-task learning. In this…
User interfaces look different across web, desktop, and mobile platforms — not just in layout, but in how buttons, icons, and text appear. This makes it hard for deep learning models trained on one platform to accurately detect UI components on another. In this paper, we evaluate the cross-domain generalization of three modern object…
