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 for example journal articles, books, reports etc.

The department also publishes technical reports which you can read more about under Technical reports.

Under PhD dissertations you will find the department's published PhD dissertations.

Publication list

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Jensen, F., Hassan, A. & Bazzi, A. (2022). A Comparison Between Nonlinear Kalman Filters for Sensorless Induction Motor Drives. Paper presented at IEEE Energy Conversion Congress and Expo (ECCE 2022), Detroit, Michigan, United States. https://doi.org/10.1109/ECCE50734.2022.9947433

Jensen, A. L., Kristensen, E. F. & Grøn Sørensen, C. (2022). Feasibility study for organic farming. Poster session presented at The XX CIGR World Congress 2022, Kyoto, Japan.

Jensen, J. C. S. & Nørremark, M. (2022). Influence of the tire pressure on yield: Fendt VarioGrip. Pictures, Video and sound recordings (digital) https://www.youtube.com/watch?v=i7pZQ41xzkI

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

Jensen, M. H., Nazari, M., Gu, C., Rasmussen, M., Dyrskog, S. E., Simonsen, C. Z., Grønhøj, M. H., Rom Poulsen, F., Rehman, N. U. & Korshoej, A. R. (2023). Reliability and Performance of the IRRAflow® System for Intracranial Lavage and Evacuation of Hematomas - A Technical Note. https://doi.org/10.1101/2023.07.07.23292372

Jensen, R. I. T., Ferwerda, J., Jørgensen, K. S., Jensen, E. R., Borg, M., Krogh, M. P., Jensen, J. B. & Iosifidis, A. (2023). A synthetic data set to benchmark anti-money laundering methods. Scientific Data, 10(1), Article 661. https://doi.org/10.1038/s41597-023-02569-2

Jensen, R. I. T. (2024). Machine Learning for Anti-money Laundering. Aarhus University.

Jensen, R. I. T. & Iosifidis, A. (2023). Fighting Money Laundering With Statistics and Machine Learning. IEEE Access, 11, 8889-8903. https://doi.org/10.1109/ACCESS.2023.3239549

Jensen, M. H., Rasmussen, M., Mohamad, N., Dyrskog, S. E., Thorup, L., Mikic, N., Wismann, J., Grønhøj, M. H., Rom Poulsen, F., Nazari, M., Rehman, N. U., Simonsen, C. Z. & Korshoej, A. R. (2023). Safety, harm, and efficacy of IRRAflow® versus external ventricular drainage for intraventricular hemorrhage: A randomized clinical trial. medRxiv. https://doi.org/10.1101/2023.07.08.23292286

Jensen, A. M. D., Schoerghofer-Queiroz, A., Ulriksen, M. D., Tcherniak, D., Damkilde, L., Talasila, P., Larsen, P. G. & Abbiati, G. (2024). Digital twin as a service for damage prognosis of offshore wind turbine foundations. In W. Desmet, B. Pluymers, D. Moens & J. del Fresno Zarza (Eds.), Proceedings of ISMA 2024 - International Conference on Noise and Vibration Engineering and USD 2024 - International Conference on Uncertainty in Structural Dynamics (pp. 4127-4141). KU Leuven, Departement Werktuigkunde.

Jensen, M., Toft Jacobsen, J., Sharifirad, I. & Boudjadar, J. (2023). Advanced Acceleration and Implementation of Convolutional Neural Networks on FPGAs. In J. Chen & L. T. Yang (Eds.), 2023 IEEE International Conference on High Performance Computing & Communications, Data Science & Systems, Smart City & Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys): Proceedings (pp. 558-565). IEEE. https://doi.org/10.1109/HPCC-DSS-SmartCity-DependSys60770.2023.00082

Jensen, R. I. T., Gerlings, J. & Ferwerda, J. (2024). Do Awareness Campaigns Reduce Financial Fraud? European Journal on Criminal Policy and Research. Advance online publication. https://doi.org/10.1007/s10610-024-09573-1

Jakobsen, M. O., Herskind, E. S., Pedersen, C. F. & Knudsen, M. B. (2023). Detecting insufficient lubrication in rolling bearings, using a low cost MEMS microphone to measure vibrations. Mechanical Systems and Signal Processing, 200, Article 110553. https://doi.org/10.1016/j.ymssp.2023.110553

Jakobsen, M. O. (2024). Detection of Lubrication Conditions in Ball Bearings Using Acoustic Ultrasound Signals. Aarhus University.

Jakobsen, M. O. (2024). Low cost MEMS accelerometer and microphone based condition monitoring sensor, with LoRa and Bluetooth Low Energy radio. HardwareX, 18, Article e00525. https://doi.org/10.1016/j.ohx.2024.e00525

Jain, A., Cunha, F., Bunsen, M. J., Cañas, J. S., Pasi, L., Pinoy, N., Helsing, F., Russo, J., Botham, M., Sabourin, M., Fréchette, J., Anctil, A., Lopez, Y., Navarro, E., Perez Pimentel, F., Zamora, A. C., Silva, J. A. R., Gagnon, J., August, T. ... Rolnick, D. (2025). Insect Identification in the Wild: The AMI Dataset. In A. Leonardis , E. Ricci , S. Roth , O. Russakovsky , T. Sattler & G. Varol (Eds.), Computer Vision – ECCV 2024 - 18th European Conference, Proceedings (pp. 55-73). Springer. https://doi.org/10.1007/978-3-031-72913-3_4

Jahangir, M. F., Schultz, C. P. L. & Kamari, A. (2024). A review of drivers and barriers of Digital Twin adoption in building project development processes. Journal of Information Technology in Construction, 29, 141-178. https://doi.org/10.36680/j.itcon.2024.008

Jahangir, M. F., Kamari, A. & Schultz, C. P. L. (2024). Developing A Building Simulation Identity Card for Enhanced Safety and Collaboration in Emergency Evacuation Simulations. In M. Srećković, M. Kassem, R. Soman & A. Chassiakos (Eds.), Proceedings of the 2024 European Conference on Computing in Construction (pp. 128-135) https://doi.org/10.35490/EC3.2024.199

Jacobsen, R. H. & Marandi, S. A. (2021). Security Threats Analysis of the Unmanned Aerial Vehicle System. In MILCOM 2021 - 2021 IEEE Military Communications Conference (pp. 316-322) https://doi.org/10.1109/MILCOM52596.2021.9652900

Jacobsen, R. H., Matlekovic, L., Shi, L., Malle, N., Ayoub, N., Hageman, K., Hansen, S., Nyboe, F. F. & Ebeid, E. (2023). Design of an Autonomous Cooperative Drone Swarm for Inspections of Safety Critical Infrastructure. Applied Sciences (Switzerland), 13(3), Article 1256. https://doi.org/10.3390/app13031256

Iversen, M., Monisha, M. & Agarwala, S. (2022). Flexible, Wearable and Fully-printed Smart Patch for pH and Hydration Sensing in Wounds. International Journal of Bioprinting, 8(1), 41-49. https://doi.org/10.18063/IJB.V8I1.447

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

Iraji, M., Dehghani, M., Mohammadi, M., Vafamand, N. & Boudjadar, J. (2021). Motor Current Signature Analysis Using Shapelet. In H. Selvaraj, G. Chmaj & D. Zydek (Eds.), Proceedings of the 27th International Conference on Systems Engineering, ICSEng 2020 (pp. 23-33). Springer. https://doi.org/10.1007/978-3-030-65796-3_3

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, Article 106277. https://doi.org/10.1016/j.compbiomed.2022.106277

Iqbal, S., Naveed, K., Naqvi, S. S., Naveed, A. & Khan, T. M. (2023). Robust retinal blood vessel segmentation using a patch-based statistical adaptive multi-scale line detector. Digital Signal Processing: A Review Journal, 139, Article 104075. https://doi.org/10.1016/j.dsp.2023.104075

Iosifidis, A. & Tefas, A. (2022). Introduction. In A. Iosifidis & A. Tefas (Eds.), Deep Learning for Robot Perception and Cognition Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00006-3

Inci, E. O., Croes, J., Desmet, W., Gomes, C., Thule, C., Lausdahl, K. & Larsen, P. G. (2021). The Effect and Selection of Solution Sequence in Co-Simulation. In C. R. Martin, M. J. Blas & A. I. Psijas (Eds.), 2021 Annual Modeling and Simulation Conference (ANNSIM) (pp. 1-12). IEEE. https://doi.org/10.23919/ANNSIM52504.2021.9552130

Inci, E. O., Desmet, W., Gomes, C. & Croes, J. (2023). Error Estimators for Adaptive Scheduling Algorithm for Serial Co-Simulation. In M. J. Blas & G. Alvarez (Eds.), 2023 Annual Modeling and Simulation Conference (ANNSIM) (pp. 73-83). IEEE. https://ieeexplore.ieee.org/document/10155365

Inceoglu, F., Hernandez Marcano, N. J., Jacobsen, R. H. & Karoff, C. (2020). A General Overview for Localizing Short Gamma-Ray Bursts with a CubeSat Mega-Constellation. Frontiers in Astronomy and Space Sciences, 7(November), Article 573060. https://doi.org/10.3389/fspas.2020.573060

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

Imanberdiyev, N., Sood, S., Kircali, D. & Kayacan, E. (2022). Design, development and experimental validation of a lightweight dual-arm aerial manipulator with a COG balancing mechanism. Mechatronics, 82, Article 102719. https://doi.org/10.1016/j.mechatronics.2021.102719

Ibrahim, I. A. F. A. H., Bochtis, D., Grøn Sørensen, C. & Nørremark, M. (2010). Automated generation of guidance lines for operational field planning. Biosystems Engineering, 107(4), 294-306. https://doi.org/10.1016/j.biosystemseng.2010.09.001

Hvilshøj, F., Iosifidis, A. & Assent, I. (2021). On Quantitative Evaluations of Counterfactuals. ArXiv. https://doi.org/10.48550/arXiv.2111.00177

Hvilshøj, F., Iosifidis, A. & Assent, I. (2021). ECINN: Efficient Counterfactuals from Invertible Neural Networks. In 32nd British Machine Vision Conference 2021, BMVC 2021, Virtual https://arxiv.org/abs/2103.13701

Huynh, H. A., Zamani, M., Ronchini, M., Farkhani, H. & Moradi, F. (2021). A 53GΩ@DC Input Impedance Multi-Channel Neural Recording Amplifier with 0.77 μvrms Input-Referred Noise for Deep Brain Implants. In 2021 IEEE Custom Integrated Circuits Conference, CICC 2021 - Proceedings Article 9431403 IEEE. https://doi.org/10.1109/CICC51472.2021.9431403

Hurst, A., Zhang, Q., Lucani Rötter, D. E. & Assent, I. (2021). Direct Analytics of Generalized Deduplication Compressed IoT Data. In 2021 IEEE Global Communications Conference, GLOBECOM 2021 - Proceedings IEEE. https://doi.org/10.1109/GLOBECOM46510.2021.9685589

Hurst, A., Lucani Rötter, D. E., Assent, I. & Zhang, Q. (2023). GLEAN: Generalized Deduplication Enabled Approximate Edge Analytics. IEEE Internet of Things Journal, 10(5), 4006-4020. https://doi.org/10.1109/JIOT.2022.3166455

Hurst, A. (2024). Analytics Directly on Compressed IoT Data. Aarhus University.

Hurst, A., Lucani Rötter, D. E. & Zhang, Q. (2024). GreedyGD: Enhanced Generalized Deduplication for Direct Analytics in IoT. IEEE Transactions on Industrial Informatics, 20(4), 6954-6962. https://doi.org/10.1109/TII.2024.3353913

Hurst, A., Lucani Rötter, D. E. & Zhang, Q. (2024). PairwiseHist: Fast, Accurate, and Space-Efficient Approximate Query Processing with Data Compression. Proceedings of the VLDB Endowment, 17(6), 1432-1445. https://doi.org/10.14778/3648160.3648181

Hudson, N., Khamfroush, H. & Lucani Rötter, D. E. (2021). QoS-Aware Placement of Deep Learning Services on the Edge with Multiple Service Implementations. In 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

Hudert, M. M., Elvebakken, M. F., Meagher, M., Mangliar, L., Zhang, X. & Esterle, L. (2022). Deep learning enhanced robotic fabrication of timber-to-timber connections with densified hardwood nails. In Proceedings of the IASS 2022 Symposium affiliated with APCS 2022 conference: Innovation - Sustainability - Legacy (pp. 1740-1748)

Huang, Q., Li, H., Liao, Y., Hao, Y. & Zhou, P. (2024). Noise-NeRF: Hide Information in Neural Radiance Field Using Trainable Noise. In M. Wand, K. Malinovská, J. Schmidhuber & I. V. Tetko (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2024 - 33rd International Conference on Artificial Neural Networks, Proceedings (pp. 320-334). Springer. https://doi.org/10.1007/978-3-031-72335-3_22

Høye, T. T., Dyrmann, M., Kjær, C., Nielsen, J., Bruus, M., Mielec, C. L., Vesterdal, M. S., Bjerge, K., Madsen, S. A., Jeppesen, M. R. & Melvad, C. (2022). Accurate image-based identification of macroinvertebrate specimens using deep learning — How much training data is needed? PeerJ, 10, Article e13837. https://doi.org/10.7717/peerj.13837

Hosseinzadeh, M., Wachal, A., Khamfroush, H. & Lucani Rötter, D. E. (2021). Optimal Accuracy-Time Trade-off For Deep Learning Services in Edge Computing Systems. In ICC 2021 - IEEE International Conference on Communications, Proceedings IEEE. https://doi.org/10.1109/ICC42927.2021.9500744

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

Hosseinzadeh, M., Hudson, N., Zhao, X., Khamfroush, H. & Lucani Rötter, D. E. (2021). Joint Compression and Offloading Decisions for Deep Learning Services in 3-Tier Edge Systems. In 2021 IEEE International Symposium on Dynamic Spectrum Access Networks, DySPAN 2021 (pp. 254-261). IEEE. https://doi.org/10.1109/DySPAN53946.2021.9677398

Hosseini, S., Laursen, K., Rashidi, A., Mondal, T., Corbett, B. & Moradi, F. (2021). S-MRUT: Sectored-Multi Ring Ultrasonic Transducer for Selective Powering of Brain Implants. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 68(1), 191-200. Article 9112273. https://doi.org/10.1109/TUFFC.2020.3001084

Horrillo-Quintero, P., Garcia-Trivino, P., Hoseinni, E., Garcia-Vazquez, C. A., Sanchez-Sainz, H., Ugalde-Loo, C. E., Peric, V. & Fernandez-Ramirez, L. M. (2024). Dynamic Fuzzy Logic Energy Management System for a Multi-Energy Microgrid. IEEE Access, 12, 93221-93234. https://doi.org/10.1109/ACCESS.2024.3422009

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Technical reports

Department of Electrical and Computer Engineering publishes technical reports covering our research areas.

With the reports, we wish to communicate the newest knowledge and research to society ahead of and during the publication process which can take up to a year.

Read the technical reports by following the link below:

Technical Report Department of Electrical and Computer Engineering

PhD dissertations

At the Department of Electrical and Computer Engineering, PhD dissertations are published via Aarhus University Library's/State and University Library's online E-books platform that is open access. You can find the published dissertations by following the link below.

PhD dissertations at Department of Electrical and Computer Engineering

AU Engineering Profile

Download AU Engineering Profile 2013-2022:

Revised 22.02.2024

AU Engineering