Publications at Department of Electrical and Computer Engineering

Under publication list you can find a complete list of the publications that are written by employees at the Publications at Department of Electrical and Computer Engineering.

Publication list

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Bochtis, D. & Grøn Sørensen, C. (2010). Agricultural fleet management: An operational research approach. In P. Savoie, J. Villeneuve & R. Morisette (Eds.), XVIIth World Congress of the International Commission of Agricultural and Biosystems Engineering, Book of Abstracts (pp. 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.

Boccardi, R., Brendstrup Møller, C., Mizushima, I., Tang, T., Davidsen, R. S., Behrensdorff Poulsen, P., dos Reis Benatto, G. A. & Thorsteinsson, S. (2025). Towards simultaneous double-side Ni/Cu plated contacts on wet etch opened TOPCon solar cells. In 2025 IEEE 53rd Photovoltaic Specialists Conference, PVSC 2025 (pp. 734-737) https://doi.org/10.1109/PVSC59419.2025.11133113

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 presented at Rhythm Production and Perception Workshop 2021, Oslo, Norway.

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

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), Article 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, Article 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. https://arxiv.org/abs/2212.00423

Bjerge, K., Frigaard, C. E. & Karstoft, H. (2023). Object Detection of Small Insects in Time-Lapse Camera Recordings. Sensors, 23(16), Article 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), Article e0000051. 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 from 2023 Butterfly Conservation Symposium, Bedfordshire , United Kingdom.

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, Article 102278. https://doi.org/10.1016/j.ecoinf.2023.102278

Bjerge, K., Bodesheim, P. & Karstoft, H. (2024). Few-Shot Learning with Novelty Detection. 340-363. Paper presented at DeLTA 2024 - 5th International Conference on Deep Learning Theory and Applications. https://doi.org/10.1007/978-3-031-66694-0_21

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, Article 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. In In Proceedings of the 20th International Joint Conference on Computer Vision (Vol. 2, pp. 286-297). Imaging and Computer Graphics Theory and Applications - VISAPP 2025. https://doi.org/10.5220/0013114600003912

Bjerge, K., Karstoft, H. & Høye, T. T. (2025). Towards edge processing of images from insect camera traps. Remote Sensing in Ecology and Conservation, 11(5), 573-589. https://doi.org/10.1002/rse2.70007

Bjerge, K. (2025). Computer Vision and Deep Learning for Insect Monitoring (1 ed.). Aarhus University.

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), Article 301. https://doi.org/10.1038/s41597-025-04579-8

Bindal, N., Rajib, M. M., Raj, R. K., Atulasimha, J. & Kaushik, B. K. (2025). Antiferromagnetic skyrmion-based energy-efficient leaky integrate and fire neuron device. Nanotechnology, 36(16), Article 165201. https://doi.org/10.1088/1361-6528/adb8c1

Biglari, R., Gomes, C. & Denil, J. (2025). TOWARDS A VALIDITY FRAME OF MULTI-MODAL SURROGATE MODELS FOR TRAFFIC SIMULATION. In S. Ferrero-Losada & A. B. Abdelnabi (Eds.), ANNSIM 2025 - Annual Modeling and Simulation Conference 2025 IEEE.

Betzer, J. S., Boudjadar, J., Frasheri, M. & Talasila, P. (2024). Digital Twin Enabled Runtime Verification for Autonomous Mobile Robots under Uncertainty. (pp. 10-17). ArXiv. https://doi.org/10.1109/DS-RT62209.2024.00012

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 ), Article 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. In 2010 4th International Conference on Pervasive Computing Technologies for Healthcare, Pervasive Health 2010 Article 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. In J. Bennedsen, K. Edström, M. S. Gudjonsdottir, I. Sæmundsdóttir, N. Kuptasthien, J. Roslöf & A. Sripakagorn (Eds.), The 17^th International CDIO Conference: Proceedings - Full papers (pp. 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. In 18th CDIO International Conference Proceedings - Full papers (pp. 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. In G. Reilly, M. Murphy, B. V. Nagy & H.-M. Jarvinen (Eds.), SEFI 2023 - 51st Annual Conference of the European Society for Engineering Education: Engineering Education for Sustainability, Proceedings (pp. 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. In L. Bettaieb, N. Ajailia, J. Bennedsen, K. Edstrom, M. N. Singh, R. Lyng, N. Maynard, J. Malmqvist & F. Bystrom (Eds.), 20th International CDIO Conference, CDIO 2024 - Proceedings (pp. 481-494). Chalmers tekniska högskola.

Bennedsen, J. & Øien, G. E. D. (2024). A unified didactic foundation for Aarhus University's tech faculty: Experiences and impact. In L. Bettaieb, N. Ajailia, J. Bennedsen, K. Edstrom, M. N. Singh, R. Lyng, N. Maynard, J. Malmqvist & F. Bystrom (Eds.), 20th International CDIO Conference, CDIO 2024 - Proceedings (pp. 458-471). Chalmers tekniska högskola.

Bennedsen, J., Roslöf, J., Øien, G. E. D., Berge, R. A., Andersen, B. & Hansen, B. L. (2025). Towards Nordic University Collaboration on Lifelong Learning for Engineers: Triangulating Stakeholder Perspectives. In R. Kangaslampi, G. Langie, H.-M. Järvinen & B. Nagy (Eds.), SEFI 2025 - 53rd Annual Conference of the European Society for Engineering Education: Engineering and Society, Proceedings (pp. 150-160). European Society for Engineering Education (SEFI). https://doi.org/10.5281/zenodo.17631873

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), Article 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. Article 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. 63-77. Paper presented at International Symposium on Intelligent and Autonomous Systems, Tallinn, Estonia. https://doi.org/10.1007/978-3-030-87657-9_5

Bechchristensen, C., Lunner, T., Harte, J., Rank, M. & Kidmose, P. (2022). Chirp-Evoked Auditory Steady-State Response: The Effect of Repetition Rate. IEEE Transactions on Biomedical Engineering, 69(2), 689-699. https://doi.org/10.1109/TBME.2021.3103332

Baxter, J., van Acker, B., Kristensen, M., Wright, T., Cavalcanti, A. & Gomes, C. (2025). Formal Architectural Patterns for Adaptive Robotic Software. In A. Boronat & G. Fraser (Eds.), Fundamental Approaches to Software Engineering. FASE 2025 (pp. 145-165). Springer. https://doi.org/10.1007/978-3-031-90900-9_8

Battle, N., Thule, C., Gonçalves Gomes, C. Â., Macedo, H. D. & Larsen, P. G. (2020). Towards a Static Check of FMUs in VDM-SL. 272-288. https://doi.org/10.1007/978-3-030-54997-8_18

Battle, N., Macedo, H. D. & Larsen, P. G. (2021). VDM Combinatorial Testing Guidelines.

Baş, E. E., Abbiati, G., Gonçalves Gomes, C. Â., Jassmann, U. & Larsen, P. G. (2024). Digitalization of Large-Scale Testing Facilities for the Wind Industry: DIGIT-BENCH Digital Twin. Journal of Physics: Conference Series, 2767(4), Article 042033. https://doi.org/10.1088/1742-6596/2767/4/042033

Barzegar Gerdroodbary, M. & Salavatidezfouli, S. (2025). A predictive surrogate model based on linear and nonlinear solution manifold reduction in cardiovascular FSI: A comparative study. Computers in Biology and Medicine, 189, Article 109959. https://doi.org/10.1016/j.compbiomed.2025.109959

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