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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Çabuk, U. C., Tosun, M., Jacobsen, R. H. & Dagdeviren, O. (2020). Path Loss Estimation of Air-to-Air Channels for FANETs over Rugged Terrains. I 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings Artikel 9302160 IEEE. https://doi.org/10.1109/SIU49456.2020.9302160

Çabuk, U. C., Tosun, M., Jacobsen, R. H. & Dagdeviren, O. (2020). A Holistic Energy Model for Drones. I 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings Artikel 9302218 IEEE. https://doi.org/10.1109/SIU49456.2020.9302218

Cabrera, A. F., Gram-Kampmann, E. M., Kappel, S. L., Remvig, L. S., Toft, H. O., Madsen, R. E., Juhl, C., Kidmose, P. & Rank, M. L. (2024). Detection of Hypoglycemia using ear-EEG. I 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024 - Proceedings IEEE. https://doi.org/10.1109/EMBC53108.2024.10781651

Brusatori, M. F. & Volet, N. (2021). Revised theory for the linewidth of diode lasers under external optical feedback. I V. S. Ilchenko, A. M. Armani, J. V. Sheldakova, A. V. Kudryashov & A. H. Paxton (red.), Laser Resonators, Microresonators, and Beam Control XXIII Artikel 1167211 SPIE - International Society for Optical Engineering. https://doi.org/10.1117/12.2583210

Brusatori, M. F. & Volet, N. (2022). Dynamics of Semiconductor Lasers under External Optical Feedback from Both Sides of the Laser Cavity. Photonics, 9(1), Artikel 43. https://doi.org/10.3390/photonics9010043

Brusatori, M. F., Duplat, D. N., Degli-Eredi, I., Nielsen, L., Tønning, P. L., Castera, P., Volet, N. & Heck, M. J. R. (2022). Ultralow-linewidth ring laser using hybrid integration and generic foundry platforms. Optics Letters, 47(11), 2686-2689. https://doi.org/10.1364/OL.457367

Bro Damsgaard, S., Hernandez Marcano, N. J., Nørremark, M., Jacobsen, R. H., Rodríguez, I. & Mogensen, P. (2022). Wireless Communications for Internet of Farming: An Early 5G Measurement Study. IEEE Access, 10, 105263-105277. https://doi.org/10.1109/ACCESS.2022.3211096

Brandt, P., Grønvig, M., Rong, L., Zhang, G., Gautam, K. R., Kristensen, J. K. & Bjerg, B. (2022). The effect of floor cooling on respiration rate and distribution of pigs in the pen. Livestock Science, 257, Artikel 104832. https://doi.org/10.1016/j.livsci.2022.104832

Bozorgasli, Z., Foroozan, H., Gheisarnejad Chirani, M. & Khooban, M. H. (2021). New Trends on Digital Twin-Based Blockchain Technology in Zero-Emission Ship Applications. Naval Engineers Journal, 133(3), 115-135. http://bt.e-ditionsbyfry.com/publication/?m=63540&i=721756&view=articleBrowser&article_id=4109541&ver=html5

Bozcan, I. & Kayacan, E. (2020). UAV-AdNet: Unsupervised Anomaly Detection using Deep Neural Networks for Aerial Surveillance. I 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (s. 1158-1164). Artikel 9341790 IEEE. https://doi.org/10.1109/IROS45743.2020.9341790

Bozcan, I., Sejersen, J. L. F., Pham, X. H. & Kayacan, E. (2021). GridNet: Image-Agnostic Conditional Anomaly Detection for Indoor Surveillance. IEEE Robotics and Automation Letters, 6(2), 1638 - 1645. Artikel 9345954. https://doi.org/10.1109/LRA.2021.3057003

Bozcan, I. & Kayacan, E. (2020). Contextual Anomaly Detection for Low Altitude Aerial Surveillance.

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

Bowen, J. P., Gomes, C. & Liu, Z. (2025). Preface. I J. P. Bowen, C. Gomes & Z. Liu (red.), Engineering Trustworthy Software Systems (s. vii-xiv). Springer.

Boudjadar, J. (2020). A Study of the Trade-off Energy Consumption-Performance-Schedulability for DVFS Multicore Systems. International Journal of Computer and Information Engineering, 14(11), 380-391.

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. & Khooban, M. H. (2021). A Safety-Driven Cost Optimization for the Real-Time Operation of a Hybrid Energy System. I H. Selvaraj, G. Chmaj & D. Zydek (red.), Proceedings of the 27th International Conference on Systems Engineering, ICSEng 2020 (s. 390-400). Springer. https://doi.org/10.1007/978-3-030-65796-3_38

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 and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-82196-8_45

Boudjadar, J. (2022). A Digital Twin Setup for Safety-aware Optimization of a Cyber-Physical System. Afhandling præsenteret på International Conference on Informatics in Control, Automation and Robotics, Lisbon, Portugal.

Boudjadar, J. (2022). A Flexible Implementation Model for Neural Networks on FPGAs. Afhandling præsenteret på International Conference on Intelligent Systems Design and Applications.

Boudjadar, J. & Schultz, C. P. L. (2023). A Knowledge-Based Proactive Intelligent System for Buildings Occupancy Monitoring. 680-687. Afhandling præsenteret på 19th International Conference on Software Technologies, Rome, Italien.

Boudjadar, J. & Islam, S. U. (2024). AgriScanNet-18: A Robust Multilayer CNN for Identification of Potato Plant Diseases. 291-308. Afhandling præsenteret på Intelligent Systems Conference, Amsterdam, Holland. https://doi.org/10.1007/978-3-031-47724-9_20

Boudjadar, J., Islam, S. U. & Buyya, R. (2025). Dynamic FPGA reconfiguration for scalable embedded artificial intelligence (AI): A co-design methodology for convolutional neural networks (CNN) acceleration. Future Generation Computer Systems, 169, Artikel 107777. https://doi.org/10.1016/j.future.2025.107777

Böttjer, T., Sandberg, M., Larsen, P. G. & Macedo, H. D. (2021). Modelling an Injection Moulding Machine using the Vienna Development Method. I H. D. Macedo, C. Thule & K. Pierce (red.), Proceedings of the 19th International Overture Workshop (s. 51-65) https://arxiv.org/abs/2110.09371

Böttjer, T., Ørnskov Rønsch, G., Gonçalves Gomes, C. Â., Ramanujan, D., Iosifidis, A. & Larsen, P. G. (2021). Data-Driven Identification of Remaining Useful Life for Plastic Injection Moulds. I A.-L. Andersen, R. Andersen, D. Brunoe, M. Stoettrup Schioenning Larsen, K. Nielsen, A. Napoleone & S. Kjeldgaard (red.), Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems: Proceedings of the Changeable, Agile, Reconﬁgurable and Virtual Production Conference and the World Mass Customization & Personalization Conference (s. 431-439). Springer. https://www.springerprofessional.de/en/data-driven-identification-of-remaining-useful-life-for-plastic-/19816878

Böttjer, T., Ørnskov Rønsch, G., Gomes, C., Ramanujan, D., Iosifidis, A. & Larsen, P. G. (2022). Data-Driven Identification of Remaining Useful Life for Plastic Injection Moulds. I A.-L. Andersen, R. Andersen, T. D. Brunoe, M. Stoettrup Schioenning Larsen, K. Nielsen, A. Napoleone & S. Kjeldgaard (red.), Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems - Proceedings of the 8th Changeable, Agile, Reconfigurable and Virtual Production Conference CARV 2021 and 10th World Mass Customization and Personalization Conference MCPC 2021 (s. 431-439). Springer. https://doi.org/10.1007/978-3-030-90700-6_49

Böttjer, T., Tola, D., Kakavandi, F., Wewer, C. R., Ramanujan, D., Gomes, C., Larsen, P. G. & Iosifidis, A. (2023). A review of unit level digital twin applications in the manufacturing industry. CIRP Journal of Manufacturing Science and Technology, 45, 162-189. https://doi.org/10.1016/j.cirpj.2023.06.011

Böttjer, T. (2024). Towards Manufacturing Digital Twins: A Case Study in the Injection Moulding Industry. Section of Electrical and Computer Engineering, Department of Engineering, Aarhus University, DK.

Borup, K., Kidmose, P., Phan, H. & Mikkelsen, K. (2023). Automatic sleep scoring using patient-specific ensemble models and knowledge distillation for ear-EEG data. Biomedical Signal Processing and Control, 81, Artikel 104496. https://doi.org/10.1016/j.bspc.2022.104496

Borges, H. B., Zaar, J., Alickovic, E., Kidmose, P. & Christensen, C. B. (2024). Speech Reception Threshold Estimation via EEG-Based Continuous Speech Envelope Reconstruction. https://doi.org/10.1101/2024.06.26.600765v1

Borges, H. B., Zaar, J., Alickovic, E., Christensen, C. B. & Kidmose, P. (2024). The Speech Reception Threshold Can be Estimated Using EEG Electrodes In and Around the Ear. https://doi.org/10.1101/2024.12.02.625819

Borges, H. B., Zaar, J., Alickovic, E., Christensen, C. B. & Kidmose, P. (2025). Speech Reception Threshold Estimation via EEG-Based Continuous Speech Envelope Reconstruction. European Journal of Neuroscience, 61(6), Artikel e70083. https://doi.org/10.1111/ejn.70083

Borges, H. B. (2025). Neural Correlates of Speech Intelligibility.

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

Bontempi, L., Zattoni, M., Ramella, A., Migliavacca, F., Ringgaard, S., Kim, W. Y., Johansen, P. & Colombo, M. (2025). Idealized aortic annuloplasty FSI digital twin of 3D-printed phantoms with 4D-flow MRI comparison. Computers in Biology and Medicine, 192, Artikel 110398. https://doi.org/10.1016/j.compbiomed.2025.110398

Böhnert, T., Rezaeiyan, Y., Claro, M. S., Benetti, L., Jenkins, A. S., Farkhani, H., Moradi, F. & Ferreira, R. (2023). Weighted spin torque nano-oscillator system for neuromorphic computing. Nature Communication Engineering, 2, Artikel 65. https://doi.org/10.1038/s44172-023-00117-9

Bogomolov, S., Fitzgerald, J., Foldager, F. F., Gamble, C., Larsen, P. G., Pierce, K., Stankaitis, P. & Wooding, B. (2021). Tuning Robotti: the Machine-assisted Exploration of Parameter Spaces in Multi-Models of a Cyber-Physical System. I J. Fitzgerald, T. Oda & H. D. Macedo (red.), Proceedings of the 18th International Overture Workshop (s. 50-65) https://arxiv.org/pdf/2101.07261.pdf

Bogomolov, S., Gomes, C., Isasa, C., Soudjani, S., Stankaitis, P. & Wright, T. (2025). Reachability analysis of FMI models using data-driven dynamic sensitivity. Simulation, 101(5), 575-596. https://doi.org/10.1177/00375497241261409

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

Bochtis, D., Sørensen, C. A. G., Jørgensen, R. N. & Green, O. (2009). Modelling of material handling operations using controlled traffic. Biosystems Engineering, 103(4), 397-408. https://doi.org/10.1016/j.biosystemseng.2009.02.006

Bochtis, D. & Grøn Sørensen, C. (2010). Agricultural fleet management: an operational research approach. Afhandling præsenteret på World Congress of the International Commission of Agricultural and Biosystems Engineering (CIGR), Quebec, Canada. http://bioeng.ca/publications/meetings-papers?sobi2Task=sobi2Details&sobi2Id=383

Bochtis, D. & Grøn Sørensen, C. (2010). Agricultural fleet management: An operational research approach. I P. Savoie, J. Villeneuve & R. Morisette (red.), XVIIth World Congress of the International Commission of Agricultural and Biosystems Engineering, Book of Abstracts (s. 212) https://www.researchgate.net/publication/267331059_AGRICULTURAL_FLEET_MANAGEMENT_AN_OPERATIONAL_RESEARCH_APPROACH

Bochtis, D., Sørensen, C. A. G., Jørgensen, R. N., Nørremark, M., Hameed, I. A. & Swain, K. C. (2011). Robotic weed monitoring. Acta Agriculturae Scandinavica, Section B - Soil & Plant Science, 61(3), 202-208. https://doi.org/10.1080/09064711003796428

Bochtis, D. D., Grøn Sørensen, C., Busato, P. & Berruto, R. (2013). Benefits from optimal route planning based on B-patterns. Biosystems Engineering, 115(4), 389-395. https://doi.org/10.1016/j.biosystemseng.2013.04.006

Bochtis, D. D., Sørensen, C. G., Fountas, S., Moysiadis, V. & Pardalos, P. M. (2022). Preface. Springer Optimization and its Applications, 184, v-xiii.

Bliddal, H., Christensen, C. B., Møller, C., Vuust, P. & Kidmose, P. (2021). Neural correlates of beat perception measured using ear-EEG: Bringing EEG music studies into the concert hall . Poster-session præsenteret på Rhythm Production and Perception Workshop 2021, Oslo, Norge.

Bliddal, H., Christensen, C. B., Møller, C., Vuust, P. & Kidmose, P. (2021). Neural correlates of beat perception measured using ear-EEG. Poster-session præsenteret på Advances and Perspectives in Auditory Neuroscience, USA.

Blasco Román, S. & Böttjer, T. (2025). A Methodological Approach to Prioritize Digital Twin Development in Manufacturing. Applied Stochastic Models in Business and Industry, 41(3), Artikel e2889. https://doi.org/10.1002/asmb.2889

Bjerge, K., Schougaard, J. H. & Larsen, D. E. (2021). A scalable and efficient convolutional neural network accelerator using HLS for a system-on-chip design. Microprocessors and Microsystems, 87, Artikel 104363. https://doi.org/10.1016/j.micpro.2021.104363

Bjerge, K., Mann, H. M. R. & Høye, T. T. (2022). Real-time insect tracking and monitoring with computer vision and deep learning. Remote Sensing in Ecology and Conservation, 8(3), 315-327. https://doi.org/10.1002/rse2.245

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