Publikationer fra instituttet

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

Publikationsliste

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Abkar, M., Zehtabiyan-Rezaie, N. & Iosifidis, A. (2023). Reinforcement learning for wind-farm flow control: Current state and future actions. Theoretical and Applied Mechanics Letters, 13(6), Artikel 100475. https://doi.org/10.1016/j.taml.2023.100475

Abrial, J. R. & Hallerstede, S. (2007). Refinement, decomposition, and instantiation of discrete models: Application to event-B. Fundamenta Informaticae, 77(1-2), 1-28. https://dl.acm.org/doi/10.5555/2366448.2366450

Oda, T., Araki, K., Sahara, S., Chang, H.-M. & Larsen, P. G. (2021). Refactoring for Exploratory Specification in VDM-SL. I H. D. Macedo, C. Thule & K. Pierce (red.), Proceedings of the 19th International Overture Workshop (s. 21-35) https://arxiv.org/abs/2110.09371

Imanberdiyev, N. & Kayacan, E. (2020). Redundancy Resolution based Trajectory Generation for Dual-Arm Aerial Manipulators via Online Model Predictive Control. I Proceedings - IECON 2020: 46th Annual Conference of the IEEE Industrial Electronics Society (s. 674-681). Artikel 9254702 IEEE. https://doi.org/10.1109/IECON43393.2020.9254702

Green, O., Lamandé, M., Schjønning, P., Sørensen, C. A. G. & Bochtis, D. (2011). Reducing the risk of soil compaction by applying "Jordværn Online"® when performing slurry distribution. Acta Agriculturae Scandinavica, Section B - Soil & Plant Science, 61(3), 209-213. https://doi.org/10.1080/09064710.2010.490535

Gheisarnejad Chirani, M., Akhbari, A., Rahimi, M., Andresen, B. & Khooban, M. H. (2022). Reducing Impact of Constant Power Loads on DC Energy Systems by Artificial Intelligence. IEEE Transactions on Circuits and Systems II: Express Briefs, 69(12), 4974-4978. https://doi.org/10.1109/TCSII.2022.3194271

Rasool, S. & Jacobsen, R. H. (2024). REC to ReCert: Introducing Re-Certification to Empower Prosumer-driven Certificate Aggregators. I 2024 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2024 (s. 77-83). IEEE. https://doi.org/10.1109/SmartGridComm60555.2024.10738030

Mukherjee, M., Kumar, V., Kumar, S., Lloret, J., Zhang, Q. & Guo, M. (2021). Reconfigurable Intelligent Surface-assisted Edge Computing to Minimize Delay in Task Offloading. I 2021 IEEE Global Communications Conference (GLOBECOM) (Bind 2021-January). IEEE. https://doi.org/10.1109/GLOBECOM46510.2021.9685374

Raj, R. K., Jony, S. H., Sengupta, P. & Shreya, S. (2026). Reconfigurable Bio-Plausible Spiking Neurons Based on Antiferromagnetic Skyrmions Utilizing Anisotropy Gradient. IEEE Magnetics Letters, 17, Artikel 4500205. https://doi.org/10.1109/LMAG.2026.3685158

Rafiei Foroushani, M., Tran, D. T. & Iosifidis, A. (2023). Recognition of Defective Mineral Wool Using Pruned ResNet Models. I H. Dorksen, S. Scanzio, J. Jasperneite, L. Wisniewski, K. F. Man, T. Sauter, L. Seno, H. Trsek & V. Vyatkin (red.), 2023 IEEE 21st International Conference on Industrial Informatics (INDIN) IEEE. https://doi.org/10.1109/INDIN51400.2023.10217993

Li, N., Iosifidis, A. & Zhang, Q. (2022). Receptive Field-based Segmentation for Distributed CNN Inference Acceleration in Collaborative Edge Computing. I ICC 2022 - IEEE International Conference on Communications (s. 4281-4286). IEEE. https://doi.org/10.1109/ICC45855.2022.9838547

Iqbal, S., Khan, T. M., Naveed, K., Naqvi, S. S. & Nawaz, S. J. (2022). Recent trends and advances in fundus image analysis: A review. Computers in Biology and Medicine, 151, Artikel 106277. https://doi.org/10.1016/j.compbiomed.2022.106277

Figueiredo, R. P. D., Sejersen, J. L. F., Hansen, J. G., Brandão, M. & Kayacan, E. (2021). Real-Time Volumetric-Semantic Exploration and Mapping: An Uncertainty-Aware Approach. (s. 9064-9070). https://doi.org/10.48550/arXiv.2109.01474

Bjerge, K., Mann, H. M. R. & Høye, T. T. (2022). Real-time insect tracking and monitoring with computer vision and deep learning. Remote Sensing in Ecology and Conservation, 8(3), 315-327. https://doi.org/10.1002/rse2.245

Oshnoei, S., Hassani, S., Gheisarnejad, M. & Mahboubi-Moghaddam, E. (2026). Real-Time Evaluation of Cyberattack-Resilient Control for Secure Large-Scale Power Networks. IEEE Internet of Things Journal, 13(3), 4449-4462. https://doi.org/10.1109/JIOT.2025.3633503

Hervella, C., Diez, L., Fernández, F., Marcano, N. J. H., Jacobsen, R. H. & Agüero, R. (2022). Realistic Assessment of Transport Protocols Performance over LEO-based Communications. I PE-WASUN '22: Proceedings of the 19th ACM International Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor & Ubiquitous Networks (s. 91-98). Association for Computing Machinery. https://doi.org/10.1145/3551663.3558680

Khan, F., Hervella, C., Diez, L., Fernández, F., Marcano, N. J. H., Jacobsen, R. H. & Agüero, R. (2023). Realistic assessment of transport protocols performance over LEO-based communications. Computer Networks, 236, Artikel 110008. https://doi.org/10.1016/j.comnet.2023.110008

Talasila, P., Mikkelsen, P. H., Gil Arboleda, S. & Larsen, P. G. (2024). Realising Digital Twins. I J. Fitzgerald, C. Gomes & P. G. Larsen (red.), The Engineering of Digital Twins (s. 225-256). Springer. https://doi.org/10.1007/978-3-031-66719-0_11

Shi, L., Pantic, M., Andersson, O., Tognon, M., Siegwart, R. & Jacobsen, R. H. (2022). Reactive Motion Planning for Rope Manipulation and Collision Avoidance using Aerial Robots. I IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022 (s. 3384-3391). IEEE. https://doi.org/10.1109/IROS47612.2022.9981658

Bogomolov, S., Gomes, C., Isasa, C., Soudjani, S., Stankaitis, P. & Wright, T. (2025). Reachability analysis of FMI models using data-driven dynamic sensitivity. Simulation, 101(5), 575-596. https://doi.org/10.1177/00375497241261409

Rask, C. D. & Lucani Rötter, D. E. (2024). RAGE for the Machine: Image Compression with Low-Cost Random Access for Embedded Applications. I 2024 IEEE International Conference on Image Processing, ICIP 2024: Proceedings (s. 1987-1993). IEEE. https://doi.org/10.1109/ICIP51287.2024.10647293

Magris, M., Shabani, M. & Iosifidis, A. (2026). Quasi black-box variational inference for Bayesian learning. Pattern Recognition, 177, Artikel 113219. https://doi.org/10.1016/j.patcog.2026.113219

Hafeez, S., Abro, G. E. M., Memon, S. A., Khan, T. A., Memon, I. & Nasir, H. (2026). Quantum-secured routing in drone communication for 6G-enabled smart mobility. Scientific Reports, 16(1), Artikel 8626. https://doi.org/10.1038/s41598-026-36297-5

Hafeez, S., Abro, G. E. M. & Marimuthu, M. (2026). Quantum-Secured AI-Driven Drone Logistics for Real-Time Healthcare Delivery. Arabian Journal for Science and Engineering. Advance online publication. https://doi.org/10.1007/s13369-026-11104-5

Gheisarnejad Chirani, M. & Khooban, M. H. (2023). Quantum Power Electronics: From Theory to Implementation. ArXiv. https://doi.org/10.48550/arXiv.2303.04763

Masoudian, A., Jakobsen, U., Hafshejani, S. F. & Khooban, M. H. (2026). Quantum-Driven Intelligent Controller Design for DC–DC Boost Converters. IEEE Journal of Emerging and Selected Topics in Power Electronics. Advance online publication. https://doi.org/10.1109/JESTPE.2026.3685135

Faurby, C. F. D., Wang, Y., Paesani, S., Ruf, F., Volet, N., Heck, M., Wieck, A. D., Ludwig, A., Midolo, L. & Lodahl, P. (2023). Quantum-Dot Single-Photon Sources Processed on Silicon-Nitride Integrated Circuits. Afhandling præsenteret på Conference on Laser and Electro-Optics (CLEO) , San Jose, California, USA.

Gheisarnejad Chirani, M. & Khooban, M. H. (2023). Quantum Deep Learning for Fast Switching of Full-Bridge Power Converters. Designs, 7(3), Artikel 60. https://doi.org/10.3390/designs7030060

Reese, F. S., Amariei, G., Henriksen, M. L., Klarskov, P. & Hinge, M. (2025). Quantitative identification of melamine flame retardant in polyolefins with hyperspectral imaging and machine learning. Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy, 333, Artikel 125870. https://doi.org/10.1016/j.saa.2025.125870

Deantoni, J., Muñoz, P., Gomes, C., Verbrugge, C., Mittal, R., Heinrich, R., Bellis, S. & Vallecillo, A. (2025). Quantifying and combining uncertainty for improving the behavior of Digital Twin Systems. Automatisierungstechnik: AT, 73(2), 81-99. https://doi.org/10.1515/auto-2024-0036

Johansen, P. (2004). Quantification of Cavitation in the Vicinity of Mechanical Heart Valves.

Amariei, G., Henriksen, M. L., Klarskov, P. & Hinge, M. (2024). Quantification of aluminium trihydrate flame retardant in polyolefins via in-line hyperspectral imaging and machine learning for safe sorting. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 311, Artikel 123984. https://doi.org/10.1016/j.saa.2024.123984

Hallerstede, S. & Hoang, T. S. (2007). Qualitative probabilistic modelling in Event-B. I Integrated Formal Methods - 6th International Conference, IFM 2007, Proceedings (s. 293-312). Springer Verlag. https://doi.org/10.1007/978-3-540-73210-5_16

Jensen, R. I. T. & Iosifidis, A. (2023). Qualifying and raising anti-money laundering alarms with deep learning. Expert Systems with Applications, 214, Artikel 119037. https://doi.org/10.1016/j.eswa.2022.119037

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

Hallerstede, S., Robby, Hatcliff, J., Belt, J. & Hardin, D. (2026). Proof Engineering in Logika: Synergistically Integrating Automated and Semi-automated Program Verification. I A. Remke & B. Steffen (red.), Formal Methods for Industrial Critical Systems - 30th International Conference, FMICS 2025, Proceedings (s. 39-58). Springer. https://doi.org/10.1007/978-3-032-00942-5_3

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. (2026). Prognosis of fall risk in home care clients: A noninvasive approach using survival analysis. Journal of Public Health (Germany), 34(4), 905-917. https://doi.org/10.1007/s10389-024-02317-9

Domini, D., Ingemann, C. O., Aguzzi, G., Esterle, L. & Viroli, M. (2026). ProFed: A Benchmark for Proximity-Based Non-IID Federated Learning. Journal of Open Research Software, 14(1), Artikel 13. https://doi.org/10.5334/jors.624

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/

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