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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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. (2025). Neural Correlates of Speech Intelligibility.

Borges, H. B. (2024). Speech-reception-threshold estimation via EEG-based continuous speech envelope reconstruction.

Borges, H. B. (2024). The Speech Reception Threshold Can be Estimated Using EEG Electrodes In and Around the Ear.

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

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

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.

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

Bjerge, K., Alison, J., Dyrmann, M., Frigaard, C. E., Mann, H. M. R. & Høye, T. T. (2022). Accurate detection and identification of insects from camera trap images with deep learning. bioRxiv. https://doi.org/10.1101/2022.10.25.513484

Bjerge, K., Frigaard, C. E. & Karstoft, H. (2022). Motion Informed Object Detection of Small Insects in Time-lapse Camera Recordings. arxiv.org.

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

Bjerge, K., Geissmann, Q., Alison, J., Mann, H. M. R., Høye, T. T., Dyrmann, M. & Karstoft, H. (2023). Hierarchical Classification of Insects with Multitask Learning and Anomaly Detection. bioRxiv. https://doi.org/10.1101/2023.06.29.546989

Bjerge, K., Alison, J., Dyrmann, M., Frigaard, C. E., Mann, H. M. R. & Høye, T. T. (2023). Accurate detection and identification of insects from camera trap images with deep learning. PLOS Sustainability and Transformation, 2(3). https://doi.org/10.1371/journal.pstr.0000051

Bjerge, K., Pinoy, N., Karstoft, H. & Høye, T. T. (2023). Field trials with automated moth monitoring in three different habitats of Denmark. Abstract fra 2023 Butterfly Conservation Symposium, Bedfordshire , Storbritannien.

Bjerge, K., Geissmann, Q., Alison, J., Mann, H. M. R., Høye, T. T., Dyrmann, M. & Karstoft, H. (2023). Hierarchical classification of insects with multitask learning and anomaly detection. Ecological Informatics, 77, Artikel 102278. https://doi.org/10.1016/j.ecoinf.2023.102278

Bjerge, K., Bodesheim, P. & Karstoft, H. (2024). Few-Shot Learning with Novelty Detection. Afhandling præsenteret på DeLTA 2024 - 5th International Conference on Deep Learning Theory and Applications.

Bjerge, K., Karstoft, H., Mann, H. M. R. & Høye, T. T. (2024). A deep learning pipeline for time-lapse camera monitoring of floral environments and insect populations. bioRxiv. https://doi.org/10.1101/2024.04.12.589205

Bjerge, K., Karstoft, H. & Høye, T. T. (2024). Towards edge processing of images from insect camera traps. bioRxiv. https://doi.org/10.1101/2024.07.01.601488

Bjerge, K., Karstoft, H., Mann, H. M. R. & Høye, T. T. (2024). A deep learning pipeline for time-lapse camera monitoring of insects and their floral environments. Ecological Informatics, 84, Artikel 102861. https://doi.org/10.1016/j.ecoinf.2024.102861

Bjerge, K., Bodesheim, P. & Karstoft, H. (2025). Deep Image Clustering with Model-Agnostic Meta-Learning. I In Proceedings of the 20th International Joint Conference on Computer Vision (Bind 2, s. 286-297). Imaging and Computer Graphics Theory and Applications - VISAPP 2025.

Bjarke Mikkelsen, K., Rezai Tabar, Y., Rævsbæk Birch, L., Kappel, S. L., Christensen, C. B., Dalskov Mosgaard, L., Otto, M., Christian Hemmsen, M., Lind Rank, M. & Kidmose, P. (2025). Ear-EEG sleep monitoring data sets. Scientific Data, 12(1), Artikel 301. https://doi.org/10.1038/s41597-025-04579-8

Betzer, J. S., Boudjadar, J., Frasheri, M. & Talasila, P. (2024). Digital Twin Enabled Runtime Verification for Autonomous Mobile Robots under Uncertainty. ArXiv. https://doi.org/10.48550/arXiv.2412.09913

Bettaieb, L., Ajailia, N., Bennedsen, J., Edström, K., Singh, M. N., Lyng, R., Maynard, N., Malmqvist, J. & Byström, F. (2024). Editorial. Proceedings of the International CDIO Conference, IV-V.

Besson, M., Alison, J., Bjerge, K., Gorochowski, T. E., Høye, T. T., Jucker, T., Mann, H. M. R. & Clements, C. F. (2022). Towards the fully automated monitoring of ecological communities. Ecology Letters, 25(12), 2753-2775. https://doi.org/10.1111/ele.14123

Berntsen, J., Rimestad, J., Lassen, J. T., Tran, D. & Kragh, M. F. (2022). Robust and generalizable embryo selection based on artificial intelligence and time-lapse image sequences. PLOS ONE, 17(2 ), Artikel e0262661. https://doi.org/10.1371/journal.pone.0262661

Bentsen, P., Nybo, J., Ring, C. & Wagner, S. (2010). Continuous healthcare: Removing the inconvenience of recharging. I 2010 4th International Conference on Pervasive Computing Technologies for Healthcare, Pervasive Health 2010 Artikel 5482263 https://doi.org/10.4108/ICST.PERVASIVEHEALTH2010.8900

Benos, L., Grøn Sørensen, C. & Bochtis, D. (2022). Field Deployment of Robotic Systems for Agriculture in Light of Key Safety, Labor, Ethics and Legislation Issues. Current Robotics Reports, 3(2), 49-56. https://doi.org/10.1007/s43154-022-00074-9

Bennedsen, J. (2021). Assessing students' professional criticism skills - a mathematics course case. I J. Bennedsen, K. Edström, M. S. Gudjonsdottir, I. Sæmundsdóttir, N. Kuptasthien, J. Roslöf & A. Sripakagorn (red.), The 17^th International CDIO Conference: Proceedings - Full papers (s. 293-302). Chulalongkorn University. http://www.cdio2021.chula.ac.th/download/CDIO2021_proceeding.pdf

Bennedsen, J., Böttjer, T. & Tola, D. (2022). Using GitHub classroom in teaching programming. I 18th CDIO International Conference Proceedings - Full papers (s. 690-702) https://www.diva-portal.org/smash/get/diva2:1705223/FULLTEXT01.pdf#page=704

Bennedsen, J., Edström, K., Guðjónsdóttir, M. S., Sæmundsdóttir, I., Kuptasthien, N., Roslöf, J. & Sripakagorn, A. (2021). Editorial. Proceedings of the International CDIO Conference, 1-2.

Bennedsen, J. & Øien, G. (2023). TRANSNATIONAL COLLABORATION ON LIFELONG LEARNING BETWEEN HIGHER ENGINEERING EDUCATION INSTITUTIONS: A UNIVERSITY PERSPECTIVE. I G. Reilly, M. Murphy, B. V. Nagy & H.-M. Jarvinen (red.), SEFI 2023 - 51st Annual Conference of the European Society for Engineering Education: Engineering Education for Sustainability, Proceedings (s. 173-182). European Society for Engineering Education (SEFI). https://doi.org/10.21427/2F51-E932

Bennedsen, J., Øien, G. E. D., Foo, E., Goh, E., Roslöf, J., Cheah, S. M. & Gelten, H. (2024). AN INTERNATIONAL UNIVERSITY PERSPECTIVE ON BARRIERS AND ENABLERS FOR LIFELONG LEARNING IN ENGINEERING. I L. Bettaieb, N. Ajailia, J. Bennedsen, K. Edstrom, M. N. Singh, R. Lyng, N. Maynard, J. Malmqvist & F. Bystrom (red.), 20th International CDIO Conference, CDIO 2024 - Proceedings (s. 481-494). Chalmers University of Technology.

Bennedsen, J. & Øien, G. E. D. (2024). A UNIFIED DIDACTIC FOUNDATION FOR AARHUS UNIVERSITY'S TECH FACULTY: EXPERIENCES AND IMPACT. I L. Bettaieb, N. Ajailia, J. Bennedsen, K. Edstrom, M. N. Singh, R. Lyng, N. Maynard, J. Malmqvist & F. Bystrom (red.), 20th International CDIO Conference, CDIO 2024 - Proceedings (s. 458-471). Chalmers University of Technology.

Benhassen, L. L., Hedensted, J. H., Sharghbin, M., Bechsgaard, T., Nielsen, S. L., Hasenkam, J. M. & Johansen, P. (2023). Comparison of aortic valve repair techniques with single- and double-ring annuloplasties. European Journal of Cardio-Thoracic Surgery, 63(5), Artikel ezad164. https://doi.org/10.1093/ejcts/ezad164

Benhassen, L. L., Hedensted, J. H., Hasenkam, J. M. & Johansen, P. (2023). Reply to Jasinski et al. European Journal of Cardio-Thoracic Surgery, 64(3), ezad312. Artikel ezad312. https://doi.org/10.1093/ejcts/ezad312

Bellman, K., Botev, J., Diaconescu, A., Esterle, L., Gruhl, C., Landauer, C., Lewis, P. R., Nelson, P. R., Pournaras, E., Stein, A. & Tomforde, S. (2021). Self-improving system integration: Mastering continuous change. Future Generation Computer Systems, 117, 29-46. https://doi.org/10.1016/j.future.2020.11.019

Beck, M. M., Boudjadar, J. & Chougui, Y. (2021). Energy Efficient Real-time Calibration of Wireless Sensor Networks for Smart Buildings. Afhandling præsenteret på International Symposium on Intelligent and Autonomous Systems, Tallinn, Estland.

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