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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Weiß., G., Pietraroia., D., Sassanelli., C. & Macedo., H. (2021). Manufacturing Process Simulation in a Hybrid Cloud Setup. I Proceedings of the 2nd International Conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2021 (s. 49-58). SCITEPRESS Digital Library. https://doi.org/10.5220/0010641700003062

Magris, M., Shabani, M. & Iosifidis, A. (2024). Manifold Gaussian Variational Bayes on the Precision Matrix. Neural Computation, 36(9), 1744-1798. https://doi.org/10.1162/neco_a_01686

Esterle, L., Montagna, S., Pianini, D., Aguzzi, G., Bellman, K. L., Ciatto, G., Contoli, C., Donati, M., Mariani, S., Rahmani, A., Savaglio, C., Storti, E., TaheriNejad, N., van der Sluis, O. & Wang, Z. (2024). MADTECC 2024: 1st Workshop on Medical Applications with Digital Twins and Edge-cloud Continuum - Welcome and Committees. I 2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) (s. 30-31). IEEE. https://doi.org/10.1109/PerComWorkshops59983.2024.10502899

Boettjer, T., Krogshave, J. T. & Ramanujan, D. (2021). Machine-specific estimation of milling energy consumption in detailed design. Journal of Manufacturing Science and Engineering, Transactions of the ASME, 143(8), Artikel 081010. https://doi.org/10.1115/1.4050179

Thoft Krogshave, J., Böttjer, T. & Ramanujan, D. (2020). Machine-Specific Energy Estimation Using the Unit Process Life Cycle Inventory (UPLCI) Model. I ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference: Volume 6: 25th Design for Manufacturing and the Life Cycle Conference (DFMLC) Artikel V006T06A031 American Society of Mechanical Engineers. https://doi.org/10.1115/DETC2020-22483

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

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

Bording, T. S., Asif, M. R., Barfod, A. S., Larsen, J. J., Zhang, B., Grombacher, D. J., Christiansen, A. V., Engebretsen, K. W., Pedersen, J. B., Maurya, P. K. & Auken, E. (2021). Machine learning based fast forward modelling of ground-based time-domain electromagnetic data. Journal of Applied Geophysics, 187, Artikel 104290. https://doi.org/10.1016/j.jappgeo.2021.104290

Deutch, F., Weiss, M. G., Wagner, S. R., Hansen, L. S., Larsen, F., Figueiredo, C., Moers, C. & Keller, A. K. (2025). Machine-Learning-Based Activity Tracking for Individual Pig Monitoring in Experimental Facilities for Improved Animal Welfare in Research. Sensors, 25(3), Artikel 785. https://doi.org/10.3390/s25030785

Faraji, B., Gheisarnejad, M., Rouhollahi, K., Esfahani, Z. & Khooban, M. H. (2021). Machine Learning Approach based on Ultra-Local Model Control for Treating Cancer Pain. I E E E Sensors Journal, 21(6), 8245-8252. Artikel 9285309. https://doi.org/10.1109/JSEN.2020.3042937

Wu, Q. F., Jochum, M., Avery, J. E., Vettoretti, G. & Nuterman, R. (2025). Machine Guided Derivation of the Atlantic Meridional Overturning Circulation (AMOC) Strength. Geophysical Research Letters, 52(3), Artikel e2024GL113454. https://doi.org/10.1029/2024GL113454

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), Artikel 1786. https://doi.org/10.3390/electronics12081786

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

Shabani, M. & Iosifidis, A. (2020). Low-Rank Temporal Attention-Augmented Bilinear Network for financial time-series forecasting. I 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 (s. 2156-2161). Artikel 9308440 IEEE. https://doi.org/10.1109/SSCI47803.2020.9308440

Spasaro, M. (2021). Low-Power Radio-Frequency Low Noise Amplifiers for Future Wireless Transceivers. Århus Universitet.

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

Ronchini, M. (2023). Low Power IC Implementation of Spiking Neural Networks for Implantable Neuromorphic Chips. Århus Universitet.

Ruf, F., Nielsen, L., Balauroiu, M., Volet, N. & Heck, M. (2022). Low-loss all-optical ns-switching for single-photon routing in scalable integrated quantum photonics. I R. G. Baets, P. O'Brien & L. Vivien (red.), Integrated Photonics Platforms II Artikel 12148-6 SPIE - International Society for Optical Engineering. https://doi.org/10.1117/12.2621540

Balauroiu, M., Ruf, F., Volet, N. & Heck, M. (2021). Low-loss all-optical ns-switching for scalable quantum photonic links. Poster-session præsenteret på Photonic Links for Quantum Technology Platforms.

Kumar, R. R., Hänsel, A., Castera, P., Volet, N. & Heck, M. J. R. (2024). Low-kappa DBR grating filters on an InP generic photonic integration foundry platform. Journal of the Optical Society of America B: Optical Physics, 41(4), 1054-1059. https://doi.org/10.1364/JOSAB.518800

Tashakor, N., Arabsalmanabadi, B., Naseri, F. & Goetz, S. (2022). Low-Cost Parameter Estimation Approach for Modular Converters and Reconfigurable Battery Systems Using Dual Kalman Filter. IEEE Transactions on Power Electronics, 37(6), 6323-6334. https://doi.org/10.1109/TPEL.2021.3137879

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

Taurone, F., Lucani Rötter, D. E., Fehér, M. & Zhang, Q. (2023). Lossless preprocessing of floating point data to enhance compression. I Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference. DCAI 2023 (s. 457–466). Springer. https://doi.org/10.1007/978-3-031-38318-2_45

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

Esterle, L. & King, D. W. (2021). Loosening Control—A Hybrid Approach to Controlling Heterogeneous Swarms. ACM Transactions on Autonomous and Adaptive Systems, 16(2), Artikel 5. https://doi.org/10.1145/3502725

Musaeus, C. S., Waldemar, G., Andersen, B. B., Høgh, P., Kidmose, P., Hemmsen, M. C., Rank, M. L., Kjær, T. W. & Frederiksen, K. S. (2022). Long-Term EEG Monitoring in Patients with Alzheimer's Disease Using Ear-EEG: A Feasibility Study. Journal of Alzheimer's Disease, 90(4), 1713-1723. https://doi.org/10.3233/JAD-220491

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), Artikel e13853. https://doi.org/10.1111/jsr.13853

Nørremark, M. & Grøn Sørensen, C. (2022). Logistic chain redesign in crop harvest processes. Poster-session præsenteret på Fremtidens Dage, Herning, Danmark.

de la Cour, J. D., Johnsen, C.-J. & Avery, J. E. (2024). Lockstep-Parallel Dualization of Surface Triangulations. I PASC '24: Proceedings of the Platform for Advanced Scientific Computing Conference Artikel 9 Association for Computing Machinery. https://doi.org/10.1145/3659914.3659923

Kuldeep, G. (2022). Lightweight Time-Series Signal Compression Period Extraction and Multiresolution using Difference Sequences. IEEE Internet of Things Journal, 9(9), 7043-7050. https://doi.org/10.1109/JIOT.2021.3113951

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

Vestergaard, R., Techel, J., Zhang, Q. & Lucani Rötter, D. E. (2022). Lightweight Compression for Severely Constrained IoT Devices. I European Wireless 2022; 27th European Wireless Conference IEEE.

Laakom, F., Chumachenko, K., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2021). Learning to ignore: rethinking attention in CNNs. I 32rd British Machine Vision Conference https://arxiv.org/pdf/2111.05684.pdf

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

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

Bozcan, I. (2021). Learning-based Anomaly Detection for Aerial Surveillance. Århus Universitet.

Oleksiienko, I. & Iosifidis, A. (2023). Layer Ensembles. I D. Comminiello & M. Scarpiniti (red.), 2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP) IEEE. https://doi.org/10.1109/MLSP55844.2023.10286005

Marandi, A., Alves, P. G. M. R., Aranha, D. F. & Jacobsen, R. H. (2024). Lattice-based Homomorphic Encryption for Privacy-Preserving Smart Meter Data Analytics. The Computer Journal, 67(5), 1687-1698. https://doi.org/10.1093/comjnl/bxad093

Munshi, M. T. & Klarskov, P. (2021). Laser Terahertz Emission Microscopy of Gold Nanorods forming a Coffee-stain Ring on a Semiconductor Surface. I 2021 46th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2021 IEEE. https://doi.org/10.1109/IRMMW-THz50926.2021.9566850

Marinoudi, V., Benos, L., Villa, C. C., Kateris, D., Berruto, R., Pearson, S., Sørensen, C. G. & Bochtis, D. (2024). Large language models impact on agricultural workforce dynamics: Opportunity or risk? Smart Agricultural Technology, 9, Artikel 100677. https://doi.org/10.1016/j.atech.2024.100677

Nørremark, M., Hansen, M. J., Børsting, C. F., Ottosen, C.-O. & Jensen, P. K., (2023). Landbrugsteknisk hjælp til besvarelse af høringssvar til Miljø- og klimateknologi 2023, Nr. 2023-0543309, 41 s., sep. 19, 2023. Rådgivningsnotat fra DCA - Nationalt Center for Fødevarer og Jordbrug

Kai, P. & Nørremark, M., (2025). Kortlægning af tekniske elementer af betydning for omlægning fra burægsproduktion til produktion af skrabe-, frilands- og økologiske æg, Nr. 2025-0796920, 21 s., mar. 26, 2025. Rådgivningsnotat fra DCA - Nationalt Center for Fødevarer og Jordbrug

Yalsavar, M., Karimaghaee, P., Sheikh-Akbari, A., Khooban, M. H., Dehmeshki, J. & Al-Majeed, S. (2022). Kernel Parameter Optimization for Support Vector Machine Based on Sliding Mode Control. IEEE Access, 10, 17003-17017. https://doi.org/10.1109/ACCESS.2022.3150001

Mortensen, A. K., Hansen, A. L. & Gislum, R. (2023). Kamera og kunstig intelligens til vurdering af sygdomstryk i sukkerroer. I Faglig beretning 2022: Verksamhetsberättelse (s. 53-56). NBR Nordic Beet Research Foundation. https://www.nordicbeet.nu/wp-content/uploads/2023/02/nbr_aarsberetning_2022.pdf

Hallerstede, S. (2006). Justifications for the event-b modelling notation. I J. Julliand & O. Kouchnarenko (red.), B 2007: Formal Specification and Development in B - 7th International Conference of B Users, Proceedings (s. 49-63). Springer Verlag. https://doi.org/10.1007/11955757_7

Nazari, M., Korshøj, A. R. & Rehman, N. U. (2024). Jump Plus AM-FM Mode Decomposition. Cornell University. https://doi.org/10.48550/arXiv.2407.07800

Nazari, M., Korshj, A. R. & Rehman, N. U. (2025). Jump Plus AM-FM Mode Decomposition. IEEE Transactions on Signal Processing, 73, 1081-1093. https://doi.org/10.1109/TSP.2025.3535822

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. I 2021 IEEE International Symposium on Dynamic Spectrum Access Networks, DySPAN 2021 (s. 254-261). IEEE. https://doi.org/10.1109/DySPAN53946.2021.9677398

Nielsen, A. H., Iosifidis, A. & Karstoft, H. (2021). IrradianceNet: Spatiotemporal Deep Learning Model for Satellite-Derived Solar Irradiance Nowcasting. Solar Energy, 228, 659-669. https://doi.org/10.1016/j.solener.2021.09.073

Amiri, M., Dehghani, M., Khayatian, A., Mohammadi, M., Vafamand, N. & Boudjadar, J. (2021). Investigation of Wind Energy Impact on Power Systems Stability Using Lyapunov Exponents. I H. Selvaraj, G. Chmaj & D. Zydek (red.), Proceedings of the 27th International Conference on Systems Engineering, ICSEng 2020 (s. 12-22). Springer. https://doi.org/10.1007/978-3-030-65796-3_2

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Ph.d.-afhandlinger ved Institut for Elektro- og Computerteknologi

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