Publikationer fra instituttet

Under publikationsliste finder du en samlet liste over de publikationer, som er lavet af medarbejdere ved Institut for Elektro- og Computerteknologi for eksempel tidsskriftsartikler, bøger, rapporter m.v.

Instituttet udgiver også tekniske rapporter, som du kan læse mere om under Tekniske rapporter.

Under ph.d.-afhandlinger finder du instituttets publicerede ph.d.-afhandlinger.

Publikationsliste

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Hosseinzadeh, M., Wachal, A., Khamfroush, H. & Lucani Rötter, D. E. (2022). QoS-Aware Priority-Based Task Offloading for Deep Learning Services at the Edge. I 2022 IEEE Annual Consumer Communications & Networking Conference (CCNC) (s. 319-325). IEEE. https://doi.org/10.1109/CCNC49033.2022.9700676

Hudson, N., Khamfroush, H. & Lucani Rötter, D. E. (2021). QoS-Aware Placement of Deep Learning Services on the Edge with Multiple Service Implementations. I 30th International Conference on Computer Communications and Networks, ICCCN 2021 IEEE. https://doi.org/10.1109/ICCCN52240.2021.9522156

Hudson, N., Khamfroush, H., Baughman, M., Lucani Rötter, D. E., Chard, K. & Foster, I. (2024). QoS-aware edge AI placement and scheduling with multiple implementations in FaaS-based edge computing. Future Generation Computer Systems, 157, 250-263. https://doi.org/10.1016/j.future.2024.03.035

Alizadeh, H., Koolivand, Y. & Sodagar, A. M. (2022). Pulse-Based, Multi-Beam Optical Link for Data Telemetry to Implantable Biomedical Microsystems. I 20th IEEE International Interregional NEWCAS Conference, NEWCAS 2022 - Proceedings (s. 529-532). IEEE. https://doi.org/10.1109/NEWCAS52662.2022.9842007

Gebreyesus, G., Cheruiyot Bett , R., Nakimbugwe, D., Hansen, L. S., Nielsen, H. M., Karstoft, H., Bjerge, K., Nkirote Kunyanga , C., MBI Tanga, C., Mwikirize, C., Akol, R., Katumba, A., Khamis, F., Kinyua, J., Walusimbi, S., Geoffrey, S., Roos, N. & Sahana, G. (2024). Prospects of implementing black soldier fly (BSF) selective breeding in Kenya and Uganda: Status from the FlyGene Project. Abstract fra Insects for the Green Economy: Sustainable Food
Systems and Livelihoods in Africa, Nairobi, Kenya. https://qgg.au.dk/fileadmin/site_files/mb/QGG/Billeder/FLYgene/book-of-abstracts-insects-for-the-green-economy-conference-feb2024.pdf

Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2023). PromptMix: Text-to-image diffusion models enhance the performance of lightweight networks. I 2023 International Joint Conference on Neural Networks (IJCNN) IEEE. https://doi.org/10.1109/IJCNN54540.2023.10191962

Heidari, N. & Iosifidis, A. (2021). Progressive Spatio-Temporal Graph Convolutional Network for Skeleton-Based Human Action Recognition. I ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (Bind 2021-June, s. 3220-3224). IEEE. https://doi.org/10.1109/ICASSP39728.2021.9413860

Heidari, N. & Iosifidis, A. (2021). Progressive Spatio-Temporal Bilinear Network with Monte Carlo Dropout for Landmark-based Facial Expression Recognition with Uncertainty Estimation. arxiv.org. https://doi.org/10.48550/arXiv.2106.04332

Heidari, N. & Iosifidis, A. (2021). Progressive Graph Convolutional Networks for Semi-Supervised Node Classification. IEEE Access, 9, 81957-81968. https://doi.org/10.1109/ACCESS.2021.3085905

Tran, D. T., Gabbouj, M. & Iosifidis, A. (2022). Progressive and compressive learning. I A. Iosifidis & A. Tefas (red.), Deep Learning for Robot Perception and Cognition (s. 187-220). Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00014-2

Lillelund, C. M., Harbo, M. & Pedersen, C. F. (2024). Prognosis of fall risk in home care clients: A noninvasive approach using survival analysis. Journal of Public Health (Germany). Advance online publication. https://doi.org/10.1007/s10389-024-02317-9

Kakavandi, F., de Reus, R., Gomes, C., Heidari, N., Iosifidis, A. & Larsen, P. G. (2022). Product Quality Control in Assembly Machine under Data Restricted Settings. I 2022 IEEE 20th International Conference on Industrial Informatics, INDIN 2022 (s. 735-741). IEEE. https://doi.org/10.1109/INDIN51773.2022.9976173

Naveed, K., Madsen, L. M., Grombacher, D. & Larsen, J. J. (2024). Processing Time-domain Induced Polarization Data Using Variational Mode Decomposition. IEEE Transactions on Geoscience and Remote Sensing, 62, 1-13. Artikel 5905713. https://doi.org/10.1109/TGRS.2024.3362290

Hallerstede, S. & Kamburjan, E. (red.) (2023). Proceedings of the Workshop on Applications of Formal Methods and Digital Twins co-located with 25th International Symposium on Formal Methods (FM 2023). CEUR-WS.org. CEUR Workshop Proceedings Bind 3507 https://ceur-ws.org/Vol-3507/

Macedo, H. D. & Pierce, K. (2023). Proceedings of the 21st International Overture Workshop. http://arxiv.org/pdf/2311.07120v2

Macedo, H. D. & Pierce, K. (red.) (2022). Proceedings of the 20th International Overture Workshop. https://doi.org/10.48550/arXiv.2208.10233

Macedo, H. D., Thule, C. & Pierce, K. (2021). Proceedings of the 19th International Overture Workshop. https://arxiv.org/abs/2110.09371

Asplund, F., Macedo, H. D. & Sassanelli, C. (2021). Problematizing the Service Portfolio of Digital Innovation Hubs. I L. M. Camarinha-Matos, X. Boucher & H. Afsarmanesh (red.), Smart and Sustainable Collaborative Networks 4.0 - 22nd IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2021, Proceedings: 22nd IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2021, Saint-Étienne, France, November 22–24, 2021, Proceedings (s. 433-440). Springer. https://doi.org/10.1007/978-3-030-85969-5_40

Zhang, S., Ding, Y., Tang, W., Sun, W., Liao, Y. & Zhou, P. Y. (2025). Privacy-Preserving Orthogonal Aggregation for Guaranteeing Gender Fairness in Federated Recommendation. I WSDM 2025 - Proceedings of the 18th ACM International Conference on Web Search and Data Mining (s. 327-335). Association for Computing Machinery, Inc.. https://doi.org/10.1145/3701551.3703513

Larsen, E. L., Espelund, U., Lauritsen, S. M., Thiesson, B., Lange, J., Friis Kjeldsen, G. & Jørgensen, M. J. (2022). +Priokritisk. Early identification of clinical detorioriation among hospitalized patients by explainable AI. Poster-session præsenteret på Symposium on Artificial Intelligence for Learning Health Systems.

Merhi, Y., Betancur, P. F., Ripolles, T. S., Suetta, C., Brage-Andersen, M. R., Hansen, S. K., Frydenlund, A., Nygaard, J. V., Mikkelsen, P. H., Boix, P. P. & Agarwala, S. (2023). Printed dry electrode for neuromuscular electrical stimulation (NMES) for e-textile. Nanoscale, 15(11), 5337-5344. https://doi.org/10.1039/d2nr06008f

Homayounzadeh, M., Homayounzade, M. & Khooban, M. H. (2024). Prescribed-time resilient current-sensorless DC power converter control. IET Power Electronics, 17(14), 2123-2133. https://doi.org/10.1049/pel2.12776

Bochtis, D. D., Sørensen, C. G., Fountas, S., Moysiadis, V. & Pardalos, P. M. (2022). Preface. Springer Optimization and its Applications, 184, v-xiii.

Riishede, I., Rode, L., Sperling, L., Overgaard, M., Ravn, J. D., Sandager, P., Skov, H., Wagner, S. R., Nørgaard, P., Clausen, T. D., Jensen, C. A. J., Pihl, K., Jørgensen, F. S., Munk, J. K., Zingenberg, H. J., Pedersen, N. G., Andersen, M. R., Wright, A., Wright, D. ... Ekelund, C. K. (2023). Pre-eclampsia Screening in Denmark (PRESIDE): National Validation Study. Obstetrical and Gynecological Survey, 78(12), 715-717. https://doi.org/10.1097/01.ogx.0001004636.48406.54

Riishede, I., Rode, L., Sperling, L., Ravn, J. D., Sandager, P., Skov, H., Wagner, S. R., Nørgaard, P., Clausen, T. D., Jensen, C. A. J., Pihl, K., Jørgensen, F. S., Munk, J. K., Zingenberg, H. J., Pedersen, N. G., Andersen, M. R., Wright, A., Wright, D., Tabor, A. & Ekelund, C. K. (2023). Pre-eclampsia screening in Denmark (PRESIDE): national validation study. Ultrasound in Obstetrics and Gynecology, 61(6), 682-690. https://doi.org/10.1002/uog.26183

Mazur-Milecka, M., Kowalczyk, N., Jaguszewska, K., Zamkowska, D., Wójcik, D., Preis, K., Skov, H., Wagner, S., Sandager, P., Sobotka, M. & Rumiński, J. (2023). Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data. I P. Strumiłło, A. Klepaczko, M. Strzelecki & D. Bociąga (red.), The Latest Developments and Challenges in Biomedical Engineering: Proceedings of the 23rd Polish Conference on Biocybernetics and Biomedical Engineering, Lodz, Poland, September 27–29, 2023 (s. 267-281). Springer. https://doi.org/10.1007/978-3-031-38430-1_21

Baltakys, K., Baltakienė, M., Heidari, N., Iosifidis, A. & Kanniainen, J. (2023). Predicting the trading behavior of socially connected investors: Graph neural network approach with implications to market surveillance. Expert Systems with Applications, 228, Artikel 120285. https://doi.org/10.1016/j.eswa.2023.120285

Shabani, M., Magris, M., Tzagkarakis, G., Kanniainen, J. & Iosifidis, A. (2023). Predicting the State of Synchronization of Financial Time Series using Cross Recurrence Plots. Neural Computing and Applications, 35(25), 18519–18531. https://doi.org/10.1007/s00521-023-08674-y

Lillelund, C. M., Pannullo, F., Jakobsen, M. O. & Pedersen, C. F. (2023). Predicting Survival Time of Ball Bearings in the Presence of Censoring. I AAAI Symposium on Survival Prediction: Algorithms, Challenges, and Applications (SPACA) AAAI Press.

Kragh, M. F., Rimestad, J., Lassen, J. T., Berntsen, J. & Karstoft, H. (2022). Predicting embryo viability based on self-supervised alignment of time-lapse videos. IEEE Transactions on Medical Imaging, 41(2), 465-475. https://doi.org/10.1109/TMI.2021.3116986

Evans, V. T., Gomes, C. & Lucani Rötter, D. E. (2025). Precision on Demand: Propositional Logic for Event-Trigger Threshold Regulation. IEEE Internet of Things Journal, 12(3), 2674-2689. https://doi.org/10.1109/JIOT.2024.3476922

D’Ambrosio, F., Harbo, M., Contiero, D., Bonfigli, A. R., Cicconi, D., Heuer, N., Roos, A., Pedersen, C. F., Fabbietti, P. & Gagliardi, C. (2024). Preact to lower the risk of falling by customized rehabilitation across Europe: the feasibility study protocol of the PRECISE project in Italy. Frontiers in Public Health, 12, Artikel 1293621. https://doi.org/10.3389/fpubh.2024.1293621

Fathollahi, A. & Andresen, B. (2025). Power Quality Analysis and Improvement of Power-to-X Plants Using Digital Twins: A Practical Application in Denmark. IEEE Transactions on Energy Conversion. Advance online publication. https://doi.org/10.1109/TEC.2025.3531113

Jeppesen, J. H., Nørremark, M. & Jacobsen, R. H. (2022). Potato Cyst Nematode Detection based on Open Satellite Data. DCA - Nationalt Center for Fødevarer og Jordbrug. Advisory report from DCA – National Center for Food and Agriculture

Schranz, T., Legaard, C. M., Tola, D. & Schweiger, G. (2021). Portable runtime environments for Python-based FMUs: Adding Docker support to UniFMU. I Proceedings of 14th Modelica Conference 2021 (s. 419-424) https://doi.org/10.3384/ecp21181419

Kamari, A., Petersen, J. H. & Schultz, C. P. L. (2021). Popularizing DGNB in the Danish construction industry: A field study of the industry via a qualitative comparative analysis. I Proceedings of the 38th International Conference of CIB W78, Luxembourg, 13-15 October: Joint Conference CIB W78 - LDAC 2021 (s. 638-649). Artikel 64. http://itc.scix.net/paper/w78-2021-paper-064

Henriksen, M. L., Karlsen, C. B., Klarskov, P. & Hinge, M. (2022). Plastic classification via in-line hyperspectral camera analysis and unsupervised machine learning. Vibrational Spectroscopy, 118, Artikel 103329. https://doi.org/10.1016/j.vibspec.2021.103329

Nørremark, M. (2022). Pilot project on precision farming. 4. Abstract fra Advances and Innovations in Agricultural Engineering., Herning, Danmark.

Merhi, Y. (2025). Piezoelectric and Crystallinity Enhancements in Poly-L-Lactide Acid (PLLA) for Bioresorbable Biomedical Sensor.

Zehtabiyan-Rezaie, N., Iosifidis, A. & Abkar, M. (2023). Physics-Guided Machine Learning for Wind-Farm Power Prediction: Toward Interpretability and Generalizability. PRX Energy, 2(1), Artikel 013009. https://doi.org/10.1103/PRXEnergy.2.013009

Rasmussen, S. M., Nielsen, T., Hody, S., Hager, H. & Schousboe, L. P. (2021). Photoplethysmography for demarcation of cutaneous squamous cell carcinoma. Scientific Reports, 11, Artikel 21467. https://doi.org/10.1038/s41598-021-00645-4

Jeppesen, J., Christensen, J., Johansen, P. & Beniczky, S. (2023). Personalized seizure detection using logistic regression machine learning based on wearable ECG-monitoring device. Seizure, 107, 155-161. https://doi.org/10.1016/j.seizure.2023.04.012

Lorenzen, K. P., Heremans, E. R. M., Vos, M. D. & Mikkelsen, K. B. (2024). Personalization of Automatic Sleep Scoring: How Best to Adapt Models to Personal Domains in Wearable EEG. IEEE Journal of Biomedical and Health Informatics, 28(10), 5804-5815. https://doi.org/10.1109/JBHI.2024.3409165

Mohammadi, S., Pahlevani, P. & Lucani, D. E. (2021). Perpetual Network Coding for Delay Sensitive Applications. Wireless Personal Communications, 120(2), 923-947. https://doi.org/10.1007/s11277-021-08497-x

Talasila, P. & Lucani Rötter, D. E. (2021). Performance of Generalized Deduplication Under Different Input Conditions. I European Wireless Conference: 26th European Wireless Conference IEEE. https://ieeexplore.ieee.org/document/9657095

Tran, D. T., Gabbouj, M. & Iosifidis, A. (2020). Performance Indicator in Multilinear Compressive Learning. I 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 (s. 1822-1828). Artikel 9308418 IEEE. https://doi.org/10.1109/SSCI47803.2020.9308418

Rahimi, M., Momenzadeh, M., Akhbari, A. & Khooban, M. H. (2023). Performance enhancement of parallel-operated inverter-based virtual synchronous generators supplying active load. IET Electric Power Applications, 17(6), 835-854. https://doi.org/10.1049/elp2.12307

Hallerstede, S. & Butler, M. (2004). Performance analysis of probabilistic action systems. Formal Aspects of Computing, 16(4), 313-331. https://doi.org/10.1007/s00165-004-0037-6

Angelov, P., Bernardi, M. L., Nardini, F. M., Pecori, R., Valerio, L., Dini, P., Ashraf, S., Aversano, L., Bianchini, M., Brutti, A., Bukovsky, I., Cagnoni, S., Cao, J., Cimitile, M., Dazzi, P., Iammarino, M., Iosifidis, A., Michahelles, F., Mora, A. ... Welsh, M. (2024). PerconAI 2024: 3rd Workshop on Pervasive and Resource-Constrained Artificial Intelligence - Welcome and Committees. I 2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) (s. 34-35). IEEE. https://doi.org/10.1109/PerComWorkshops59983.2024.10503466

Pham, X. H., Sarabakha, A., Odnoshyvkin, M. & Kayacan, E. (2022). PencilNet: Zero-Shot Sim-to-Real Transfer Learning for Robust Gate Perception in Autonomous Drone Racing. IEEE Robotics and Automation Letters, 7(4), 11847 - 11854. https://doi.org/10.1109/LRA.2022.3207545

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