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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Stanton, E. J., Tønning, P., Ulsig, E. Z., Calmar, S., Stanton, M. A., Thomsen, S. T., Gravesen, K. B., Johansen, P. & Volet, N. (2024). Continuous-wave second-harmonic generation in the far-UVC pumped by a blue laser diode. Scientific Reports, 14(1), Artikel 3238. https://doi.org/10.1038/s41598-024-53144-7

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

Dong, L., Yang, W., Wen, L., Zhao, X., Claus, A. G. S., Wu, C. & Zhou, K. (2024). Continuous curvature wayline generation using quadratic optimisation for agricultural machine guidance. Biosystems Engineering, 238, 22-37. https://doi.org/10.1016/j.biosystemseng.2023.12.009

Hedegaard Morsing, L., Bakhtiarnia, A. & Iosifidis, A. (2022). Continual Transformers: Redundancy-Free Attention for Online Inference. The Eleventh International Conference on Learning Representations. https://arxiv.org/abs/2201.06268

Hedegaard Morsing, L., Heidari, N. & Iosifidis, A. (2023). Continual Spatio-Temporal Graph Convolutional Networks. Pattern Recognition, 140(C), Artikel 109528. https://doi.org/10.1016/j.patcog.2023.109528

Qiao, Z., Pham, X. H., Ramasamy, S., Jiang, X., Kayacan, E. & Sarabakha, A. (2024). Continual Learning for Robust Gate Detection under Dynamic Lighting in Autonomous Drone Racing. I IJCNN 2024 Conference Proceedings IEEE. https://doi.org/10.1109/ijcnn60899.2024.10649903

Hedegaard, L. & Iosifidis, A. (2023). Continual Inference: A Library for Efficient Online Inference with Deep Neural Networks in PyTorch. I L. Karlinsky, T. Michaeli & K. Nishino (red.), Computer Vision – ECCV 2022 Workshops, Proceedings (s. 21-34). Springer. https://doi.org/10.1007/978-3-031-25082-8_2

Hedegaard Morsing, L. & Iosifidis, A. (2022). Continual 3D Convolutional Neural Networks for Real-time Processing of Videos. I S. Avidan, G. Brostow, M. Cissé, G. M. Farinella & T. Hassner (red.), Computer Vision – ECCV 2022 - 17th European Conference, 2022, Proceedings (s. 369-385). Springer. https://doi.org/10.1007/978-3-031-19772-7_22

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

Legaard, C. M., Schranz, T., Schweiger, G., Drgona, J., Falay, B., Gomes, C., Iosifidis, A., Abkar, M. & Larsen, P. G. (2023). Constructing Neural Network Based Models for Simulating Dynamical Systems. ACM Computing Surveys, 55(11), 1-34. Artikel 236. https://doi.org/10.1145/3567591

Swain, K. C., Zaman, Q. U., Schumann, A. W., Percival, D. C. & Bochtis, D. (2010). Computer vision system for wild blueberry fruit yield mapping. Biosystems Engineering, 106(4), 389-394. https://doi.org/10.1016/j.biosystemseng.2010.05.001

Rafiei Foroushani, M., Raitoharju, J. & Iosifidis, A. (2023). Computer Vision on X-Ray Data in Industrial Production and Security Applications: A Comprehensive Survey. IEEE Access, 11, 2445 - 2477. https://doi.org/10.1109/ACCESS.2023.3234187

Nawoya, S., Geissmann, Q., Karstoft, H., Bjerge, K., Akol, R., Katumba, A., Mwikirize, C. & Gebreyesus, G. (2024). Computer-vision based prediction of body traits and larval sex in black soldier fly. Abstract fra Insects for the Green Economy: Sustainable Food
Systems and Livelihoods in Africa, Nairobi, Kenya. https://qgg.au.dk/fileadmin/site_files/mb/QGG/Billeder/FLYgene/book-of-abstracts-insects-for-the-green-economy-conference-feb2024.pdf

Nawoya, S., Ssemakula, F., Akol, R., Geissmann, Q., Karstoft, H., Bjerge, K., Mwikirize, C., Katumba, A. & Gebreyesus, G. (2024). Computer vision and deep learning in insects for food and feed production: A review. Computers and Electronics in Agriculture, 216, Artikel 108503. https://doi.org/10.1016/j.compag.2023.108503

Agerskov, J., Nielsen, K. & Pedersen, C. F. (2023). Computationally Efficient Labeling of Cancer-Related Forum Posts by Non-Clinical Text Information Retrieval. SN Computer Science, 4(6), Artikel 711. https://doi.org/10.1007/s42979-023-02244-8

Schaper, M.-M. A., Smith, R. C., Tamashiro, M. A., Van Mechelen, M., Lunding, M. S., Bilstrup, K.-E. K., Kaspersen, M. H., Jensen, K. L., Petersen, M. G. & Iversen, O. S. (2022). Computational Empowerment in Practice: Scaffolding teenagers’ learning about emerging technologies and their ethical and societal impact. International Journal of Child - Computer Interaction, 34, Artikel 100537. https://doi.org/10.1016/j.ijcci.2022.100537

Kuldeep, G. & Zhang, Q. (2020). Compressive Sensing based Multi-class Privacy-preserving Cloud Computing. I 2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings Artikel 9348093 IEEE. https://doi.org/10.1109/GLOBECOM42002.2020.9348093

Asif, M. R., Larsen, J. J., Maurya, P. K., Christiansen, A. V. & Auken, E. (2021). Complete automation of time-domain transient electromagnetic data processing using deep convolutional autoencoder. Abstract fra AGU 2021, USA.

Meldgaard Madsen, L., Asif, M. R., Maurya, P. K., Kühl, A. K., Domenzain, D., Jensen, C., Martin, T., Bastani, M. & Persson, L. (2023). Comparison of tTEM-IP and ERT-IP: Cases from Mine Tailing Sites in Sweden. Abstract fra NSG2023 29th European Meeting of Environmental and Engineering Geophysics, Edinburgh , Storbritannien. https://doi.org/10.3997/2214-4609.202320114

Ferro, M. V., Sørensen, C. G. & Catania, P. (2024). Comparison of different computer vision methods for vineyard canopy detection using UAV multispectral images. Computers and Electronics in Agriculture, 225, Artikel 109277. https://doi.org/10.1016/j.compag.2024.109277

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

Andersen, S., Laursen, P. H., Wood, G. J., Lyhne, M. D., Madsen, T. L., Hansen, E. S. S., Johansen, P., Kim, W. Y. & Andersen, M. J. (2024). Comparison of admittance and cardiac magnetic resonance generated pressure-volume loops in a porcine model. Physiological Measurement, 45(5), Artikel 055014. https://doi.org/10.1088/1361-6579/ad4a03

Asif, M. R., Kass, M. A., Herpe, M., Rawlinson, Z., Westerhoff, R., Larsen, J. J. & Christiansen, A. V. (2025). Comparative analysis of deep learning and traditional airborne electromagnetic data processing: A case study. Geophysics, 90(3), WA103-WA112. https://doi.org/10.1190/geo2024-0282.1

Glukhov, A., Bridarolli, D., Ricci, S., Li, R., Shreya, S., Farkhani, H., Moradi, F. & Ielmini, D. (2023). Compact Modeling of Resistive Switching Memory (RRAM) With Voltage and Temperature Dependences. I 2023 IEEE Nanotechnology Materials and Devices Conference (NMDC) (s. 793-797). IEEE. https://doi.org/10.1109/NMDC57951.2023.10343984

Armacki, A., Milosevic, N., Bajovic, D., Kar, S., Jakovetic, D., Bakhtiarnia, A., Esterle, L., Muscat, A. & Festi, T. (2023). Communication efficient model-aware federated learning for visual crowd counting and density estimation in smart cities. I 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings (s. 875-879). European Signal Processing Conference, EUSIPCO. https://doi.org/10.23919/EUSIPCO58844.2023.10289938

Strøm, J., Engholm, A. L., Lorenzen, K. P. & Mikkelsen, K. B. (2024). Common sleep data pipeline for combined data sets. PLOS ONE, 19(8), Artikel e0307202. https://doi.org/10.1371/journal.pone.0307202

Zhang, B., Yan, S., Li, B., Wu, S., Feng, H., Gao, X., Song, X. & Siddique, K. H. M. (2023). Combining organic and chemical fertilizer plus water-saving system reduces environmental impacts and improves apple yield in rainfed apple orchards. Agricultural Water Management, 288, Artikel 108482. https://doi.org/10.1016/j.agwat.2023.108482

Esterle, L. (2022). Collaborative Systems: Learning and Working Together. CEUR Workshop Proceedings, 3461.

Li, N., Iosifidis, A. & Zhang, Q. (2022). Collaborative edge computing for distributed CNN inference acceleration using receptive field-based segmentation. Computer Networks, 214, Artikel 109150. https://doi.org/10.1016/j.comnet.2022.109150

Fiorelli, R., Peralías, E., Méndez-Romero, R., Rajabali, M., Kumar, A., Zahedinejad, M., Åkerman, J., Moradi, F., Serrano-Gotarredona, T. & Linares-Barranco, B. (2023). CMOS Front End for Interfacing Spin-Hall Nano-Oscillators for Neuromorphic Computing in the GHz Range. Electronics, 12(1), Artikel 230. https://doi.org/10.3390/electronics12010230

Vang, M. Ø., Grombacher, D., Larsen, J. J. & Christiansen, A. V. (2024). Clustering on SNMR and TEM parameters over a saline-freshwater interface to resolve hydrogeological layers. I NSG2024, 30th European Meeting of Environmental and Engineering Geophysics (s. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420102

Lillelund, C. M., Jensen, H. B. & Pedersen, C. F. (2022). Cloud K-SVD for Image Denoising. SN Computer Science, 3, Artikel 151. https://doi.org/10.1007/s42979-022-01042-y

Nielsen, A. H., Iosifidis, A. & Karstoft, H. (2021). CloudCast: A Satellite-Based Dataset and Baseline for Forecasting Clouds. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 3485-3494. Artikel 9366908. https://doi.org/10.1109/JSTARS.2021.3062936

Rafiei Foroushani, M. & Iosifidis, A. (2023). Class-Specific Variational Auto-Encoder for Content-Based Image Retrieval. I 2023 International Joint Conference on Neural Networks (IJCNN) IEEE. https://doi.org/10.1109/IJCNN54540.2023.10191068

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

Kappel, S. L. & Kidmose, P. (2022). Characterization of Dry-Contact EEG Electrodes and an Empirical Comparison of Ag/AgCl and IrO₂ Electrodes. I 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (s. 3127-3130). IEEE. https://doi.org/10.1109/EMBC48229.2022.9871923

Chen, J., Liang, Y. C., Cheng, H. V. & Yu, W. (2023). Channel Estimation for Reconfigurable Intelligent Surface Aided Multi-User mmWave MIMO Systems. IEEE Transactions on Wireless Communications, 22(10), 6853-6869. https://doi.org/10.1109/TWC.2023.3246264

Mousaei, A., Gheisarnejad, M. & Khooban, M. H. (2023). Challenges and opportunities of FACTS devices interacting with electric vehicles in distribution networks: A technological review. Journal of Energy Storage, 73, Artikel 108860. https://doi.org/10.1016/j.est.2023.108860

Oakes, B. J., Zhang, H., Hatledal, L. I., Feng, H., Frasheri, M., Sandberg, M., Gil Arboleda, S. & Gomes, C. (2024). Case Studies in Digital Twins. I J. Fitzgerald, C. Gomes & P. G. Larsen (red.), The Engineering of Digital Twins (s. 257-310). Springer. https://doi.org/10.1007/978-3-031-66719-0_12

Wagner, S. (2021). CARIOT+ Care Coach – An Ambient Assisted Living Ecosystem for Supporting Open Data and Open Science Projects. I E. Pissaloux, G. A. Papadopoulos, A. Achilleos & R. Velázquez (red.), ICT for Health, Accessibility and Wellbeing - 1st International Conference, IHAW 2021, Revised Selected Papers (s. 45-59). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-94209-0_5

Mehndiratta, M., Camci, E. & Kayacan, E. (2021). Can deep models help a robot to tune its controller? A step closer to self-tuning model predictive controllers. Electronics, 10(18), Artikel 2187. https://doi.org/10.3390/electronics10182187

Dyrmann, M., Mortensen, A. K., Linneberg, L., Høye, T. T. & Bjerge, K. (2021). Camera Assisted Roadside Monitoring for Invasive Alien Plant Species Using Deep Learning. Sensors (Switzerland), 21(18), Artikel 6126. https://doi.org/10.3390/s21186126

Gomes, C., Feng, H., Kazemi, Z. & Pierce, K. (2024). Calibration of Models for Digital Twins. I J. Fitzgerald, C. Gomes & P. G. Larsen (red.), The Engineering of Digital Twins (s. 129-146). Springer. https://doi.org/10.1007/978-3-031-66719-0_6

Frasheri, M., Lumer-Klabbers, G., Kvistgaard, J. L., Hausted, J. O., Thule, C., Esterle, L. & Larsen, P. G. (2023). Building Safer Robots: From Simulation to Hardware Deployment. 2023 27th International Conference on Methods and Models in Automation and Robotics, MMAR 2023 - Proceedings, 63-68. https://doi.org/10.1109/MMAR58394.2023.10242467

Robinson, C., Bagnato, A., Pastrone, C., Weyer, T., Popov, P., Macedo, H. D., Sassanelli, C., Larsen, P. G., Luz, C. H., Henshaw, M., Buron, C., Akerkar, R. & Györffi, M. (2021). Bridging the stakeholder communities that produce cyber-physical systems. I M. D. E. al (red.), HiPEAC Vision 2021: High performance embedded architecture and compilation (s. 20-29). HiPEAC. https://www.hipeac.net/vision/2021/

Villadsen, K., Dalgaard Jensen, M., Larsen, P. G. & Macedo, H. D. (2022). Bridging the Requirements-Specification Gap using Behaviour-Driven Development. I H. D. Macedo & K. Pierce (red.), Proceedings of the 20th International Overture Workshop (s. 19-33) https://doi.org/10.48550/arXiv.2208.10233

Lotlikar, V. S., Satpute, N. & Gupta, A. (2022). Brain Tumor Detection Using Machine Learning and Deep Learning: A Review. Current Medical Imaging, 18(6), 604-622. https://doi.org/10.2174/1573405617666210923144739

Nielsen, L. & Heck, M. (2021). Boosting the output power and wall-plug efficiency of lasers on a generic InP platform. I S. M. García-Blanco & P. Cheben (red.), Integrated Optics: Devices, Materials, and Technologies XXV (Bind 11689). Artikel 116890T SPIE - International Society for Optical Engineering. https://doi.org/10.1117/12.2581908

Hallerstede, S. (2022, jun. 14). Book review: Decision Procedures – An Algorithmic Point of View. (2 udg.) Springer Berlin, Heidelberg. Texts in Theoretical Computer Science. An EATCS Series https://www.fmeurope.org/2022/06/14/book-review-decision-procedures-an-algorithmic-point-of-view/

Maalandish, M., Hosseini, S. H., Sabahi, M., Rostami, N. & Khooban, M. H. (2023). B-MIMO high step-up DC/DC converter with high capability to control inputs. IET Power Electronics, 16(9), 1499-1513. https://doi.org/10.1049/pel2.12486

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