| LSTM-RNN-based defect classification in honeycomb structures using infrared thermography C Hu, Y Duan, S Liu, Y Yan, N Tao, A Osman, C Ibarra-Castanedo, ... Infrared Physics & Technology 102, 103032, 2019 | 87 | 2019 |
| Quantitative evaluation of optical lock-in and pulsed thermography for aluminum foam material Y Duan, S Huebner, U Hassler, A Osman, C Ibarra-Castanedo, ... Infrared Physics & Technology 60, 275-280, 2013 | 75 | 2013 |
| Multi-task faster R-CNN for nighttime pedestrian detection and distance estimation X Dai, J Hu, H Zhang, A Shitu, C Luo, A Osman, S Sfarra, Y Duan Infrared Physics & Technology 115, 103694, 2021 | 58 | 2021 |
| A Deep Learning Method for the Impact Damage Segmentation of Curve-Shaped CFRP Specimens Inspected by Infrared Thermography Z Wei, HC Fernandes, HG Herrmann, JR Tarpani, A Osman Sensors 21(2):395, 2021 | 49 | 2021 |
| Next Generation NDE-Sensor Systems as IIoT Elements of Industry 4.0 B Valeske, A Osman, F Romer, R Tschuncky Research in Nondestructive Evaluation 31 (5), 2020 | 40 | 2020 |
| An infrared-induced terahertz imaging modality for foreign object detection in a lightweight honeycomb composite structure H Zhang, S Sfarra, A Osman, K Szielasko, C Stumm, M Genest, ... IEEE Transactions on Industrial Informatics 14 (12), 5629-5636, 2018 | 37 | 2018 |
| Interactive Deep Learning for Shelf Life Prediction of Muskmelons Based on an Active Learning Approach. D Albert-Weiss, A Osman Sensors, 2022 | 34 | 2022 |
| Semantic wireframe detection Y Zhou, A Osman, M Willms, A Kunz, S Philipp, J Blatt, S Eul Ndt. net DGZfP 2023, 1-20, 2023 | 31 | 2023 |
| Improvement of X-ray castings inspection reliability by using Dempster–Shafer data fusion theory A Osman, V Kaftandjian, U Hassler Pattern Recognition Letters 32 (2), 168-180, 2011 | 31 | 2011 |
| Enhanced infrared image processing for impacted carbon/glass fiber-reinforced composite evaluation H Zhang, NP Avdelidis, A Osman, C Ibarra-Castanedo, S Sfarra, ... Sensors 18 (1), 45, 2017 | 29 | 2017 |
| Eddy current pulsed thermography for ballistic impact evaluation in basalt-carbon hybrid composite panels H Zhang, S Sfarra, A Osman, F Sarasini, U Netzelmann, S Perilli, ... Applied optics 57 (18), D74-D81, 2018 | 21 | 2018 |
| Automated evaluation of three dimensional ultrasonic datasets A Osman PQDT-Global, 2013 | 21 | 2013 |
| Terahertz amplitude polynomial principle component regression for aramid–basalt hybrid composite laminate inspection H Zhang, S Sfarra, A Osman, K Szielasko, C Stumm, F Sarasini, C Santulli, ... IEEE Transactions on Industrial Informatics 14 (12), 5601-5609, 2018 | 18 | 2018 |
| An automated data processing method dedicated to 3D ultrasonic non destructive testing of composite pieces A Osman, U Hassler, V Kaftandjian, J Hornegger IOP conference series: materials science and engineering 42 (1), 012005, 2012 | 18 | 2012 |
| Automated defect detection in non-planar objects using deep learning algorithms Y Tao, C Hu, H Zhang, A Osman, C Ibarra-Castanedo, Q Fang, S Sfarra, ... Journal of Nondestructive Evaluation 41 (1), 14, 2022 | 17 | 2022 |
| Pulsed thermography dataset for training deep learning models Z Wei, A Osman, B Valeske, X Maldague Applied Sciences 13 (5), 2901, 2023 | 16 | 2023 |
| Genetic cancer ovary MA Osman Clinical Ovarian and Other Gynecologic Cancer 7 (1-2), 1-7, 2014 | 16 | 2014 |
| Evaluating thermal properties of sugarcane bagasse-based composites by using active infrared thermography and terahertz imaging AO Chulkov, S Sfarra, H Zhang, A Osman, K Szielasko, C Stumm, ... Infrared Physics & Technology 97, 432-439, 2019 | 14 | 2019 |
| Application of data fusion theory and support vector machine to X-ray castings inspection A Osman, V Kaftandjian, U Hassler Proceedings of 10th European Conference on Non-Destructive Testing (ECNDT …, 2010 | 14 | 2010 |
| Artificial intelligence for defect detection in infrared images of solid oxide fuel cells Z Wei, A Osman, D Gross, U Netzelmann Infrared Physics & Technology 119, 103815, 2021 | 13 | 2021 |
Stefano SfarraAssociate Professor, University of L'AquilaПотвърден имейл адрес: univaq.it
