Publications
Ruxandra Stoean, Leonard Ionescu, Catalin Stoean, Marinela Boicea, Miguel Atencia, Gonzalo Joya, A Deep Learning-based Surrogate for the XRF Approximation of Elemental Composition within Archaeological Artefacts before Restoration, 25th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES), Procedia Computer Science, vol. 192, pp. 2002-2011, https://doi.org/10.1016/j.procs.2021.08.206, 2021.
Catalin Stoean, Leonard Ionescu, Ruxandra Stoean, Marinela Boicea, Miguel Atencia, Gonzalo Joya, A convolutional neural network as a proxy for the XRF approximation of the chemical composition of archaeological artefacts in the presence of inter-microscope variability, 16th International Work-Conference on Artificial Neural Networks (IWANN), LNCS 12862, pp. 260-271, https://doi.org/10.1007/978-3-030-85099-9_21, 2021.
Ruxandra Stoean, Leonard Ionescu, Cătălin Stoean, Marinela Boicea, Alina-Maria Gărău, Cristina-Camelia Ghițescu, Artificial intelligence can “see” the chemical composition of archaeological objects before restoration, 8th International Conference on Matter and Materials in/for Heritage Conservation (MATCONS), pp. 279 - 287, ISSN 2810 – 2797, 2021.
Ruxandra Stoean, Nebojsa Bacanin, Leonard Ionescu, Marinela Boicea, Alina-Maria Garau, Cristina-Camelia Ghitescu, Semantic Segmentation for Corrosion Detection in Archaeological Artefacts before Restoration, 23rd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), pp. 246-251, ISBN 978-1-6654-0650-5, DOI: 10.1109/SYNASC54541.2021.00049, 2021.
Cristian Daniel Alecsa, A theoretical and empirical study of new adaptive algorithms with additional momentum steps and shifted updates for stochastic non-convex optimization, submitted to Journal of Machine Learning Research, https://arxiv.org/abs/2110.08531, 2021.
Nebojsa Bacanin, Ruxandra Stoean, Miodrag Zivkovic, Aleksandar Petrovic, Tarik A. Rashid, Timea Bezdan, Performance of Novel Chaotic Firefly Algorithm with Enhanced Exploration for Tackling Global Optimization Problems: Application for Dropout Regularization, Mathematics, 9(21), 2705; https://doi.org/10.3390/math9212705, 2021.
Leonard Ionescu, The Relevance of Identity and the Restoration of a Cabinet Gramophone, Studia Universitatis Cibiniensis. Series Historica (Scopus), XVIII, 289 - 304, 2021.
Ruxandra Stoean, Nebojsa Bacanin, Leonard Ionescu, Catalin Stoean, Marinela Boicea, Alina-Maria Garau, Cristina-Camelia Ghitescu, Deep learning for a swift non-invasive recognition and delineation of corrosive iron compounds present on the surface of unrestored archaeological artefacts, 26th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, https://doi.org/10.1016/j.procs.2022.09.186, Procedia Computer Science, vol. 207, pp. 1303-1311, 2022.
Nebojsa Bacanin, Catalin Stoean, Miodrag Zivkovic, Dijana Jovanovic, Milos Antonijevic, Djordjie Mladenovic, Multi-Swarm Algorithm for Extreme Learning Machine Optimization. Sensors, 22(11):4204; https://doi.org/10.3390/s22114204, May 2022.
Leonard Ionescu, Ruxandra Stoean, Cătălin Stoean, Marinela Boicea, Alina-Maria Gărău, Cristina-Camelia Ghițescu, When Artificial Intelligence Technology and Cultural Heritage Intersect, The 12th International Conference "Youth and Museums", 2022.
Catalin Stoean, Nebojsa Bacanin, Ruxandra Stoean, Leonard Ionescu, Cristian Alecsa, Mircea Hotoleanu, Miguel Atencia, Gonzalo Joya, On Using Perceptual Loss within the U-Net Architecture for the Semantic Inpainting of Textile Artefacts with Traditional Motifs, 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), pp. 276-283, 2022.
Carlos Cano Domingo, Nuria Novas Castellano, Ruxandra Stoean, Manuel Fernandez Ros and Jose A. Gazquez Parra, Schumann resonance modes and ionosphere parameters: An annual variability comparison, IEEE Transactions on Instrumentation & Measurement, vol. 71, pp. 1-10, https://doi.org/10.1109/TIM.2022.3194912, 2022.
Leonard Ionescu, The restoration of a Klingsor pathephone. Restoration - conservation, cultural valorization, The International Symposium "The rescue, Scientific Restoration and Preservation of Heritage Values", 2022.
Leonard Ionescu, Zeno Karl Pinter, Restaurarea unor obiecte funerare descoperite în necropola de la Capidava, Studia Universitatis Cibiniensis. Series Historica (Scopus), 2022.
Cano Domingo, Ruxandra Stoean, Gonzalo Joya Caparrós, Nuria Novas Castellano, Manuel Fernandez Ros, Jose Antonio Gázquez Parra, A Machine Learning hourly analysis on the relation the Ionosphere and Schumann Resonance Frequency, Measurement, vol. 208, 112426, https://doi.org/10.1016/j.measurement.2022.112426, 2023.
Carlos Cano, Ruxandra Stoean, Gonzalo Joya Caparros, Nuria Novas, Manuel Fernandez-Ros, Jose A. Gazquez Parra, A Deep Learning Approach for enhancing the Lorentzian Curve Fit algorithm for Schumann Resonance, submitted, 2022.
Ruxandra Stoean, Nebojsa Bacanin Catalin Stoean, Leonard Ionescu, Miguel Atencia Gonzalo Joya, Computational Framework for the Evaluation of the Composition and Degradation State of Metal Heritage Assets by Deep Learning, Journal of Cultural Heritage, vol. 64, pp. 198-206, 2023.
Cristian Alecsa, OF-AE: Oblique Forest AutoEncoders, http://dx.doi.org/10.48550/arXiv.2301.00880, International Conference on Artificial Intelligence Applications and Innovations (AIAI 2023), IFIP Advances in Information and Communication Technology, vol 676, pp. 207–219, Springer, Cham, https://doi.org/10.1007/978-3-031-34107-6_17, 2023.
Carlos Cano Domingo, Ruxandra Stoean, Gonzalo Joya Caparrós, Nuria Novas Castellano, Manuel Fernandez Ros and José A. Gázquez Parra, Deep Learning event detector based on long-term Schumann Resonance signal variation, submitted, 2023.
Ruxandra Stoean, Patricio García Báez, Carmen Paz Suárez Araujo, Nebojsa Bacanin, Miguel Atencia, Catalin Stoean, Automatic Control of Class Weights in the Semantic Segmentation of Corrosion Compounds on Archaeological Artefacts, International Work-Conference on Artificial Neural Networks (IWANN 2023), Advances in Computational Intelligence, pp. 467–478, https://doi.org/10.1007/978-3-031-43078-7_382023, 2023.
Catalin Stoean, Nebojsa Bacanin, Zeev Volkovich, Leonard Ionescu, Ruxandra Stoean, Study on Semantic Inpainting Deep Learning Models for Artefacts with Traditional Motifs, International Work-Conference on Artificial Neural Networks (IWANN 2023), Advances in Computational Intelligence, pp. 479–490, https://doi.org/10.1007/978-3-031-43078-7_39, 2023.
Catalin Stoean, Nebojsa Bacanin, Ruxandra Stoean, Leonard Ionescu, Alina-Maria Gărău, Cristina-Camelia Ghițescu, Influence of Manual Inter-Observer Variability for the Performance of Deep Learning Models in Semantic Segmentation, International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC 2023), 2023.
Leonard Ionescu, Ruxandra Stoean, Catalin Stoean, Marinela Boicea, Alina-Maria Garau, Cristina-Camelia Ghitescu, Intersecția dintre tehnologia inteligenței artificiale (IA) și patrimoniul cultural, Revista de Restaurare, Conservare și Investigații a Muzeului Național de Istorie a României, nr. 3, 2023.
Leonard Ionescu, Restaurarea fierului arheologic, Simpozionul Internațional DROBETA, 2023.
Leonard Ionescu, Techniques, materials and methods of restoration-conservation of mineralized iron cultural goods, Simpozionul Internațional Arta restaurării patrimoniului cultural. Provocări și soluții, Buletinul Centrului de Restaurare Conservare Iași, nr. 1 și nr. 2/2023.
Ruxandra Stoean, Nebojsa Bacanin, Catalin Stoean, Leonard Ionescu, Bridging the Past and Present: AI-Driven 3D Restoration of Degraded Artefacts for Museum Digital Display, Journal of Cultural Heritage, submitted, 2023.