Publications at Department of Electrical and Computer Engineering

Under publication list you can find a complete list of the publications that are written by employees at the Publications at Department of Electrical and Computer Engineering.

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Laakom, F., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2023). Learning Distinct Features Helps, Provably. In D. Koutra, C. Plant, M. Gomez Rodriguez, E. Baralis & F. Bonchi (Eds.), Machine Learning and Knowledge Discovery in Databases: Research Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part II (pp. 206-222). Springer. https://doi.org/10.1007/978-3-031-43415-0_13

Heidari, N. & Iosifidis, A. (2023). Learning Diversified Feature Representations for Facial Expression Recognition in the Wild. ArXiv. https://doi.org/10.48550/arXiv.2210.09381

Kuldeep, G. & Zhang, Q. (2023). Lightweight electrocardiogram signal compression. Biomedical Signal Processing and Control, 85, Article 105012. https://doi.org/10.1016/j.bspc.2023.105012

Jørgensen, S. D., Kidmose, P., Mikkelsen, K., Blech, M., Hemmsen, M. C., Rank, M. L. & Kjaer, T. W. (2023). Long-term ear-EEG monitoring of sleep – A case study during shift work. Journal of Sleep Research, 32(5), Article e13853. https://doi.org/10.1111/jsr.13853

Alvarez Tunon, O., Brodskiy, Y. & Kayacan, E. (2023). Loss it right: Euclidean and riemannian metrics in learning-based visual odometry. In ISR Europe 2023: 56th International Symposium on Robotics, in cooperation with Fraunhofer IPA September 26 – 27, 2023 in Stuttgart (pp. 107-111). VDE Verlag GmbH. https://ieeexplore.ieee.org/abstract/document/10363060

Taurone, F., Lucani Rötter, D. E., Fehér, M. & Zhang, Q. (2023). Lossless preprocessing of floating point data to enhance compression. In R. Mehmood, V. Alves, I. Praça, J. Wikarek, J. Parra-Domínguez, R. Loukanova, I. de Miguel, T. Pinto, R. Nunes & M. Ricca (Eds.), Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference. DCAI 2023 (pp. 457–466). Springer. https://doi.org/10.1007/978-3-031-38318-2_45

Ronchini, M. (2023). Low Power IC Implementation of Spiking Neural Networks for Implantable Neuromorphic Chips. [PhD thesis, Aarhus University]. Aarhus Universitet.

Shreya, S., Rezaeiyan, Y., Sadeghi, M., Kaushik, B. K. & Moradi, F. (2023). Low-Power Pattern Recognition System Using Spintronics Compute-in-memory Architecture. In 2023 IEEE Nanotechnology Materials and Devices Conference (NMDC) (pp. 730-734). IEEE. https://doi.org/10.1109/NMDC57951.2023.10344005

Phan, H., Lorenzen, K. P., Heremans, E., Chen, O. Y., Tran, M. C., Koch, P., Mertins, A., Baumert, M., Mikkelsen, K. B. & De Vos, M. (2023). L-SeqSleepNet: Whole-cycle Long Sequence Modeling for Automatic Sleep Staging. IEEE Journal of Biomedical and Health Informatics, 27(10), 4748-4757. https://doi.org/10.1109/JBHI.2023.3303197

Islam, M. T., Khan, H. A., Naveed, K., Nauman, A., Gulfam, S. M. & Kim, S. W. (2023). LUVS-Net: A Lightweight U-Net Vessel Segmentor for Retinal Vasculature Detection in Fundus Images. Electronics, 12(8), Article 1786. https://doi.org/10.3390/electronics12081786

Khezri, R., Razmi, P., Mahmoudi, A., Bidram, A. & Khooban, M. H. (2023). Machine Learning-based Sizing of a Renewable-Battery System for Grid-Connected Homes with Fast-Charging Electric Vehicle. IEEE Transactions on Sustainable Energy, 14(2), 837-848. https://doi.org/10.1109/TSTE.2022.3227003

Oshnoei, S., Fathollahidehkordi, A., Oshnoei, A. & Khooban, M. H. (2023). Microgrid Frequency Regulation Based on a Fractional Order Cascade Controller. Fractal and Fractional, 7(4), Article 343. https://doi.org/10.3390/fractalfract7040343

Madsen, M. L., Ulsig, E. Z., Folsach, S., Godoy, P. H., Stanton, E. J. & Volet, N. (2023). Mid-infrared difference-frequency generation in AlGaAs-on-insulator waveguides. Journal of the Optical Society of America B: Optical Physics, 40(7), 1742-1748. https://doi.org/10.1364/JOSAB.488065

Nørremark, M., Hansen, M. J., Kai, P., Børsting, C. F., Ottosen, C.-O., Konnerup, D., Jensen, P. K. & Melander, B. (2023). Miljø- og Klimateknologi 2023. DCA - Nationalt Center for Fødevarer og Jordbrug. Rådgivningsrapport fra DCA - Nationalt Center for Fødevarer og Jordbrug DCA rapport No. 221 https://dcapub.au.dk/djfpublikation/djfpdf/DCArapport221.pdf

Alvarez Tunon, O., Kanner, H., Ribeiro Marnet, L., Pham, X. H., Sejersen, J. L. F., Brodskiy, Y. & Kayacan, E. (2023). MIMIR-UW: A Multipurpose Synthetic Dataset for Underwater Navigation and Inspection. In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 6141-6148). IEEE. https://doi.org/10.1109/IROS55552.2023.10341436

Hageman, K., Feal, A., Gamba, J., Girish, A., Bleier, J., Lindorfer, M., Tapiador, J. & Vallina-Rodriguez, N. (2023). Mixed Signals: Analyzing Software Attribution Challenges in the Android Ecosystem. IEEE Transactions on Software Engineering, 49(4), 2964-2979. https://doi.org/10.1109/TSE.2023.3236582

Wang, Z., Chen, L., Chen, H. & Rehman, N. U. (2023). Monthly ship price forecasting based on multivariate variational mode decomposition. Engineering Applications of Artificial Intelligence, 125, Article 106698. https://doi.org/10.1016/j.engappai.2023.106698

Kazemi, Z., Rask, J. K., Gomes, C., Yildiz, E. & Larsen, P. G. (2023). Movable factory—A systematic literature review of concepts, requirements, applications, and gaps. Journal of Manufacturing Systems, 69, 189-207. https://doi.org/10.1016/j.jmsy.2023.06.008

Lechuga, M. M. L., Nørremark, M., Jorguseski, L., D'Acunto, L., Politis, C. & Palattella, M. R. (2023). Multi-Connectivity for Livestock Transport in Rural Areas. Paper presented at 2023 Joint EuCNC & 6G Summit, Gothenburg, Sweden.

Fathollahidehkordi, A., Gheisarnejad Chirani, M., Boudjadar, J., Derakhshandeh, S. Y. & Khooban, M. H. (2023). Multi-Criteria Design of Electric Transit Bus Based on Wireless Charging Infrastructure: A Case Study of Real Road Map in Wakefield. Automation , 4(3), 291-308. https://doi.org/10.3390/automation4030017

Fathollahidehkordi, A. & Andresen, B. (2023). Multi-Machine Power System Transient Stability Enhancement Utilizing a Fractional Order-Based Nonlinear Stabilizer. Fractal and Fractional, 7(11), 808. Article 808. https://doi.org/10.3390/fractalfract7110808

Ronchini, M., Rezaeiyan, Y., Zamani, M., Panuccio, G. & Moradi, F. (2023). NET-TEN: a silicon neuromorphic network for low-latency detection of seizures in local field potentials. Journal of Neural Engineering, 20(3), Article 036002. https://doi.org/10.1088/1741-2552/acd029

Yildirim, B., Razmi, P., Fathollahidehkordi, A., Gheisarnejad Chirani, M. & Khooban, M. H. (2023). Neuromorphic deep learning frequency regulation in stand-alone microgrids. Applied Soft Computing, 144, Article 110418. https://doi.org/10.1016/j.asoc.2023.110418

Nørremark, M., Hansen, M. J., Kai, P., Børsting, C. F., Ottosen, C.-O. & Konnerup, D., (2023). Notat vedrørende miljø- og klimateknologier 2023 – del 1, No. 2023-0505187, 21 p., Jun 02, 2023. Rådgivningsnotat fra DCA - Nationalt Center for Fødevarer og Jordbrug

Noor, M. A., Benhassen, L. L., Kaspersen, A. E., Weiss, M. G., Hasenkam, J. M. & Johansen, P. (2023). Novel Expansible Aortic Annuloplasty Ring Exhibits Similar Characteristics as the Dacron Ring—an In Vitro Evaluation. Journal of Cardiovascular Translational Research, 16(5), 1144-1152. https://doi.org/10.1007/s12265-023-10393-7

Bjerge, K., Frigaard, C. E. & Karstoft, H. (2023). Object Detection of Small Insects in Time-Lapse Camera Recordings. Sensors, 23(16), Article 7242. https://doi.org/10.3390/s23167242

Fehér, M. (2023). On Compression for the Complete IoT Data Lifecycle: From Collection to Analytics. [PhD thesis, Aarhus University]. Aarhus Universitet.

Hansen, E. M., Thomsen, I. K., Cronin, I. V., Gislum, R., Larsen, R. & Mortensen, A. K., (2023). Opdatere trappemodel om dækningsgrad af efterafgrøder ved kontrol i forhold til etableringstidspunkt, No. 2022-0445946, 18 p., Apr 26, 2023. Rådgivningsnotat fra DCA - Nationalt Center for Fødevarer og Jordbrug

Vahdanjoo, M., Gislum, R. & Grøn Sørensen, C. (2023). Operational, Economic, and Environmental Assessment of an Agricultural Robot in Seeding and Weeding Operations. AgriEngineering, 5(1), 299–324. Article 5. https://doi.org/10.3390/agriengineering5010020

Fathollahidehkordi, A., Gheisarnejad Chirani, M., Boudjadar, J., Homayounzadeh, M. & Khooban, M. H. (2023). Optimal Design of Wireless Charging Electric Buses-Based Machine Learning: A Case Study of Nguyen-Dupuis Network. I E E E Transactions on Vehicular Technology, 72(7), 8449-8458. https://doi.org/10.1109/TVT.2023.3247838

Pham, X. H., Heiß, M., Tran, D., Nguyen, M. A., Nguyen, A. Q. & Kayacan, E. (2023). ORB-Net: End-to-end Planning Using Feature-based Imitation Learning for Autonomous Drone Racing. In ISR Europe 2023: 56th International Symposium on Robotics, in cooperation with Fraunhofer IPA September 26 – 27, 2023 in Stuttgart (pp. 16-21). VDE Verlag GmbH. https://ieeexplore.ieee.org/document/10363048

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

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

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), Article 013009. https://doi.org/10.1103/PRXEnergy.2.013009

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

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

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, Article 120285. https://doi.org/10.1016/j.eswa.2023.120285

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. In P. Strumiłło, A. Klepaczko, M. Strzelecki & D. Bociąga (Eds.), 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 (pp. 267-281). Springer. https://doi.org/10.1007/978-3-031-38430-1_21

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

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

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

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

Hallerstede, S. & Kamburjan, E. (Eds.) (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 Vol. 3507 https://ceur-ws.org/Vol-3507/

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

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

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

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. Paper presented at Conference on Laser and Electro-Optics (CLEO) , San Jose, California, United States.

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

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, Article 110008. https://doi.org/10.1016/j.comnet.2023.110008

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

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