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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Kumar, R. R., Nielsen, L., Volet, N. & Heck, M. (2023). Intra-cavity coherent combining of DBR lasers on an InP generic foundry platform. Optics Letters, 48(7), 1614-1617. https://doi.org/10.1364/OL.483889

Haldrup, M., Rasmussen, M., Mohamad, N., Dyrskog, S., Thorup, L., Mikic, N., Wismann, J., Grønhøj, M., Poulsen, F. R., Nazari, M., Rehman, N. U., Simonsen, C. Z. & Korshøj, A. R. (2023). Intraventricular Lavage vs External Ventricular Drainage for Intraventricular Hemorrhage: A Randomized Clinical Trial. JAMA network open, 6(10), e2335247. Artikel e2335247. https://doi.org/10.1001/jamanetworkopen.2023.35247

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

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/

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

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

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

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

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, Artikel 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), Artikel 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. 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

Taurone, F., Lucani Rötter, D. E., Fehér, M. & Zhang, Q. (2023). Lossless preprocessing of floating point data to enhance compression. I R. Mehmood, V. Alves, I. Praça, J. Wikarek, J. Parra-Domínguez, R. Loukanova, I. de Miguel, T. Pinto, R. Nunes & M. Ricca (red.), 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

Ronchini, M. (2023). Low Power IC Implementation of Spiking Neural Networks for Implantable Neuromorphic Chips. [Ph.d.-afhandling, Aarhus Universitet]. 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. I 2023 IEEE Nanotechnology Materials and Devices Conference (NMDC) (s. 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), Artikel 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), Artikel 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 Nr. 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. I 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (s. 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, Artikel 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. Afhandling præsenteret på 2023 Joint EuCNC & 6G Summit, Gothenburg, Sverige.

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. Artikel 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), Artikel 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, Artikel 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, Nr. 2023-0505187, 21 s., 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), Artikel 7242. https://doi.org/10.3390/s23167242

Fehér, M. (2023). On Compression for the Complete IoT Data Lifecycle: From Collection to Analytics. [Ph.d.-afhandling, Aarhus Universitet]. 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, Nr. 2022-0445946, 18 s., 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. Artikel 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. I ISR Europe 2023: 56th International Symposium on Robotics, in cooperation with Fraunhofer IPA September 26 – 27, 2023 in Stuttgart (s. 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), Artikel 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. I 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, Artikel 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. I P. Strumiłło, A. Klepaczko, M. Strzelecki & D. Bociąga (red.), 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 (s. 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. (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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