Aarhus Universitets segl

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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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 (s. 1-6). 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
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. [Ph.d.-afhandling, Aarhus Universitet]. Aarhus Universitet.
Esfahani, Z., Derakhshan, A. & Ramprasad, S. (2025). Lcoe Reduction in African Off-Grid Rural Microgrids: a Systematic Approach Using Dsm and Innovative Bchp Integration. I 2025 IEEE PES Conference on Innovative Smart Grid Technologies - Middle East (ISGT Middle East) IEEE. https://doi.org/10.1109/ISGTMiddleEast65737.2025.11314274
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
Bozorgtabar, B., Mahapatra, D., Roy , S., Naseer, M., Razzak, I. & Ge, Z. (Accepteret/In press). LATA: Laplacian-Assisted Transductive Adaptation for Conformal Uncertainty in Medical VLMs. I Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition IEEE. https://arxiv.org/pdf/2602.17535
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
Jiang, X., Gao, Y., Xu, H., Zhang, Q., Liao, Y. & Zhou, P. Y. (2025). Knowledge Rumination for Client Utility Evaluation in Heterogeneous Federated Learning. I 2025 IEEE International Conference on Multimedia and Expo: Journey to the Center of Machine Imagination, ICME 2025 - Conference Proceedings IEEE Computer Society Press. https://doi.org/10.1109/ICME59968.2025.11210094
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
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
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
Amarloo, A., Cinnella, P., Iosifidis, A., Forooghi, P. & Abkar, M. (2023). Investigation of Data-driven algebraic Reynolds stress models for turbulent secondary flows. I The 14th International ERCOFTAC Symposium on Engineering Turbulence Modelling and Measurements Proceedings https://www.ercoftac.org/etmm/program/conference-program/
Rafiei Foroushani, M. & Nørremark, M. (2025). Investigation of available ground-truth data in Denmark that can be used for remote identification and localization of populations of selected plant species. DCA - Nationalt Center for Fødevarer og Jordbrug. Rådgivningsrapport fra DCA - Nationalt Center for Fødevarer og Jordbrug
Khare, S. K., Khan, A. M., Bajaj, V. & Sinha, G. R. (2023). Introduction to smart healthcare and the role of cognitive sensors. I G. R. Sinha & V. Bajaj (red.), Cognitive Sensors: Applications in smart healthcare (Bind 2, s. 1-21). IOP Publishing. https://doi.org/10.1088/978-0-7503-5346-5ch1
Feng, H., Gomes, C., Thule, C., Lausdahl, K., Iosifidis, A. & Larsen, P. G. (2021). Introduction to Digital Twin Engineering. I C. R. Martin, M. J. Blas & A. I. Psijas (red.), 2021 Annual Modeling and Simulation Conference (ANNSIM) (s. 1-12). IEEE. https://doi.org/10.23919/ANNSIM52504.2021.9552135
Iosifidis, A. & Tefas, A. (2022). Introduction. I A. Iosifidis & A. Tefas (red.), Deep Learning for Robot Perception and Cognition Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00006-3
Kavanagh, S. R., Nielsen, R. S., Hansen, J. L., Davidsen, R. S., Hansen, O., Samli, A. E., Vesborg, P. C. K., Scanlon, D. O. & Walsh, A. (2025). Intrinsic point defect tolerance in selenium for indoor and tandem photovoltaics. Energy and Environmental Science, 18(9), 4431-4446. https://doi.org/10.1039/d4ee04647a
Liu, Q., Zheng, Y., Wu, H., Michalek, L., Ronchini, M., Mow, R. K., Wang, W., Park, H., Ji, X., Yu, Z., Yao, Z. F., Nishio, Y., Zhao, C., Pei, J. & Bao, Z. (2026). Intrinsically stretchable complementary circuits based on direct photo-patternable polymer semiconductors. Nature Electronics, 9(5), 507-518. https://doi.org/10.1038/s41928-026-01599-z
Kakavandi, F., Han, P., de Reus, R., Larsen, P. G. & Zhang, H. (2023). Interpretable Fault Detection Approach With Deep Neural Networks to Industrial Applications. I 2023 International Conference on Control, Automation and Diagnosis (ICCAD 2023) IEEE. https://doi.org/10.1109/ICCAD57653.2023.10152435
David, I., Shao, G., Gomes, C., Tilbury, D. & Zarkout, B. (2025). Interoperability of Digital Twins: Challenges, Success Factors, and Future Research Directions. I T. Margaria & B. Steffen (red.), Leveraging Applications of Formal Methods, Verification and Validation. Specification and Verification - 12th International Symposium, ISoLA 2024, Proceedings (s. 27-46). Springer Science+Business Media. https://doi.org/10.1007/978-3-031-75390-9_3
Skov, H., Riishede Christiansen, I. L., Rode, L., Pihl, K., Jørgensen, F. S., Zingenberg, H., Nørgaard, P., Gros Pedersen, N. M., Gjerris, A. C. R., Wagner, S. R., Tabor, A., Ekelund, C. K. & Sandager, P. (2022). Inter-arm blood pressure difference in early pregnancy and risk of preeclampsia. Abstract fra FMF 19th World Congress 2022, Kreta, Grækenland. https://fetalmedicine.org/abstracts/2022/var/pdf/abstracts/2022/04236.pdf
Laakom, F., Raitoharju, J., Nikkanen, J., Iosifidis, A. & Gabbouj, M. (2021). INTEL-TAU: A Color Constancy Dataset. IEEE Access, 9, 39560-39567. Artikel 9371681. https://doi.org/10.1109/ACCESS.2021.3064382
Boudjadar, J. & Beck, M. M. (2021). Intelligent Time Synchronization Protocol for Energy Efficient Sensor Systems. Afhandling præsenteret på Intelligent Systems Conference , Amsterdam, Holland.
Boudjadar, J. & Beck, M. M. (2022). Intelligent Time Synchronization Protocol for Energy Efficient Sensor Systems. I K. Arai (red.), Intelligent Systems and Applications - Proceedings of the 2021 Intelligent Systems Conference IntelliSys (s. 609-623). Springer Science+Business Media. https://doi.org/10.1007/978-3-030-82196-8_45