| Cost-sensitive learning classification strategy for predicting product failures FD Frumosu, AR Khan, H Schiøler, M Kulahci, M Zaki, ... Expert Systems with Applications 161, 113653, 2020 | 26 | 2020 |
| Big data analytics using semi‐supervised learning methods FD Frumosu, M Kulahci Quality and Reliability Engineering International 34 (7), 1413-1423, 2018 | 22 | 2018 |
| Outliers detection using an iterative strategy for semi‐supervised learning FD Frumosu, M Kulahci Quality and Reliability Engineering International 35 (5), 1408-1423, 2019 | 13 | 2019 |
| Rejoinder - Experiences with Big Data: Accounts from a Data Scientist’s Perspective M Kulahci, FD Frumosu, A Rauf Khan, G Ørnskov Rønsch, MP Spooner Quality Engineering 32 (4), 563-565, 2020 | 9* | 2020 |
| Initial value problems for nonlinear differential equations solved by differential transform method, I M Cîrnu, FD Frumosu Journal of Information Systems and Operations Management 3 (1), 102-107, 2009 | 9 | 2009 |
| Automated vision-based inspection of mould and part quality in soft tooling injection moulding using imaging and deep learning Y Zhang, S Shan, FD Frumosu, M Calaon, W Yang, Y Liu, HN Hansen CIRP Annals 71 (1), 429-432, 2022 | 7 | 2022 |
| Mould wear-out prediction in the plastic injection moulding industry: a case study FD Frumosu, GØ Rønsch, M Kulahci International Journal of Computer Integrated Manufacturing 33 (12), 1245-1258, 2020 | 6 | 2020 |
| Online monitoring for error detection in vat photopolymerization FD Frumosu, M Méndez Ribó, S Shan, Y Zhang, M Kulahci International Journal of Computer Integrated Manufacturing 36 (9), 1313-1330, 2023 | 4 | 2023 |
| Initial value problems for nonlinear differential equations solved by differential transform method, II MI Cîrnu, FD Frumosu Journal of Information Systems and Operations Management 3 (2), 381-387, 2009 | 3 | 2009 |
| Interpretability by design using computer vision for behavioral sensing in child and adolescent psychiatry FD Frumosu, NN Lønfeldt, ARC Mora-Jensen, S Das, NL Lund, ... arXiv preprint arXiv:2207.04724, 2022 | 2 | 2022 |
| Beyond Accuracy: Fairness, Scalability, and Uncertainty Considerations in Facial Emotion Recognition L Fromberg, T Nielsen, FD Frumosu, LH Clemmensen Northern Lights Deep Learning Conference, 67-74, 2024 | 1 | 2024 |
| Vision-guided robotic automation of vat polymerization additive manufacturing production: design, calibration and verification W Yang, JK Crone, CR Lønkjær, MM Ribo, S Shan, FD Frumosu, ... Journal of Intelligent Manufacturing and Special Equipment, 2023 | 1 | 2023 |
| Computational behavior recognition in child and adolescent psychiatry: a statistical and machine learning analysis plan NN Lønfeldt, FD Frumosu, ARC Mora-Jensen, NL Lund, S Das, ... arXiv preprint arXiv:2205.05737, 2022 | 1 | 2022 |
| COMPUTATIONAL BEHAVIOR RECOGNITION IN CHILD AND NN Lønfeldt, FD Frumosu, ARC Mora-Jensen, NL Lund, S Das, ... arXiv preprint arXiv:2205.05737, 2022 | | 2022 |
| Investigation on semi-virtual dataset based semantic segmentation for injection moulding process monitoring S Shan, FD Frumosu, MM Ribo, M Calaon, Y Zhang 22nd International Conference of the European Society for Precision …, 2022 | | 2022 |
| Data analysis methods for process understanding and improvement in injection moulding production FD Frumosu Technical University of Denmark, 2019 | | 2019 |
| Dynamic stability of rotors considering parameter uncertainties FD Frumosu | | 2013 |
| VIBRATION DAMPING USING LASER VIBROMETRY INVESTIGATED WITH THE ANOVA METHOD DAN SPOREA, FD FRUMOSU Advanced Mathematical And Computational Tools In Metrology And Testing IX …, 2012 | | 2012 |
| The crustal uplift determined at the Jakobshavn glacier (West Greenland) using ATM and GPS data IS Muresan, FD Frumosu, SA Khan Grøn dyst 2012, 2012 | | 2012 |
| euspen’s 22nd International Conference & Exhibition, Geneva, CH, May/June 2022 G Olea, N Huber, J Zeeb | | |
