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 for example journal articles, books, reports etc.

The department also publishes technical reports which you can read more about under Technical reports.

Under PhD dissertations you will find the department's published PhD dissertations.

Publication list

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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

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

Tola, D., Gonçalves Gomes, C. Â., Schultz, C. P. L., Schlette, C., Hansen, C. & Esterle, L. (2021). RoboCIM: Towards a Domain Model for Industrial Robot System Configurators. In A. Soylu, A. T. Nezhad, N. Nikolov, I. Toma, A. Fensel & J. Vennekens (Eds.), Proceedings of the 15th International Rule Challenge, 7th Industry Track, and 5th Doctoral Consortium @ RuleML+RR 2021 co-located with 17th Reasoning Web Summer School (RW 2021) and 13th DecisionCAMP 2021 as part of Declarative AI 2021 CEUR-WS.org. http://ceur-ws.org/Vol-2956/paper12.pdf

Frasheri, M., Ejersbo, H., Thule, C. & Esterle, L. (2021). RMQFMU: Bridging the Real World with Co-simulation For Practitioners. In H. D. Macedo, C. Thule & K. Pierce (Eds.), Proceedings of the 19th International Overture Workshop (pp. 66-80) https://arxiv.org/pdf/2110.09371.pdf

Mukherjee, M., Kumar, V., Kumar, S., Mavromoustakis, C. X., Zhang, Q. & Guo, M. (2022). RIS-assisted Task Offloading for Wireless Dead Zone to Minimize Delay in Edge Computing. In 2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings (pp. 2554-2559). IEEE. https://doi.org/10.1109/GLOBECOM48099.2022.10001478

Yazdani, N. & Lucani Rötter, D. E. (2021). Revolving Codes: Overhead and Computational Complexity Analysis. IEEE Communications Letters, 25(2), 374-378. Article 9210058. https://doi.org/10.1109/LCOMM.2020.3027875

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

Shekar, S., Satpute, N. & Gupta, A. (2021). Review on diabetic retinopathy with deep learning methods. Journal of Medical Imaging, 8(6), Article 060901. https://doi.org/10.1117/1.JMI.8.6.060901

Niazi, K. A. K., Yang, Y. & Sera, D. (2019). Review of mismatch mitigation techniques for PV modules. IET Renewable Power Generation, 13(12), 2035-2050. https://doi.org/10.1049/iet-rpg.2019.0153

Kremer, T., Irons, T., Müller-Petke, M. & Juul Larsen, J. (2022). Review of Acquisition and Signal Processing Methods for Electromagnetic Noise Reduction and Retrieval of Surface Nuclear Magnetic Resonance Parameters. Surveys in Geophysics, 43(4), 999-1053. https://doi.org/10.1007/s10712-022-09695-3

Chumachenko, K., Laakom, F., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2021). Rethinking compactness in deep neural networks. Paper presented at International Conference on Machine Learning Workshop on Overparameterization. https://drive.google.com/file/d/1pu5xJMPvKuGFeVCcylEvLz00uLK3UN9I/view

Heidari, N. (2022). Representation Learning for Graph-Structured Data Analysis. Aarhus Universitet.

Kjær, T. W., Rank, M. L., Hemmsen, M. C., Kidmose, P. & Mikkelsen, K. (2022). Repeated automatic sleep scoring based on ear-EEG is a valuable alternative to manually scored polysomnography. PLOS Digital Health, 1(10), Article e0000134. https://doi.org/10.1371/journal.pdig.0000134

Larsen, J. J., Lévy, L. & Asif, M. R. (2022). Removal of powerline noise in geophysical data sets with a scientific machine-learning based approach. IEEE Transactions on Geoscience and Remote Sensing, 60, Article 5923410. https://doi.org/10.1109/TGRS.2022.3223737

Tran, D. T., Gabbouj, M. & Iosifidis, A. (2022). Remote Multilinear Compressive Learning with Adaptive Compression. IEEE Internet of Things Journal, 9(9), 6905-6913. Advance online publication. https://doi.org/10.1109/jiot.2021.3114743

Jensen, M. H., Nazari, M., Gu, C., Rasmussen, M., Dyrskog, S. E., Simonsen, C. Z., Grønhøj, M. H., Rom Poulsen, F., Rehman, N. U. & Korshoej, A. R. (2023). Reliability and Performance of the IRRAflow® System for Intracranial Lavage and Evacuation of Hematomas - A Technical Note. medRxiv : the preprint server for health sciences https://doi.org/10.1101/2023.07.07.23292372

Oda, T., Araki, K., Sahara, S., Chang, H-M. & Larsen, P. G. (2021). Refactoring for Exploratory Specification in VDM-SL. In H. D. Macedo, C. Thule & K. Pierce (Eds.), Proceedings of the 19th International Overture Workshop (pp. 21-35) https://arxiv.org/abs/2110.09371

Imanberdiyev, N. & Kayacan, E. (2020). Redundancy Resolution based Trajectory Generation for Dual-Arm Aerial Manipulators via Online Model Predictive Control. In Proceedings - IECON 2020: 46th Annual Conference of the IEEE Industrial Electronics Society (pp. 674-681). Article 9254702 IEEE. https://doi.org/10.1109/IECON43393.2020.9254702

Green, O., Lamandé, M., Schjønning, P., Sørensen, C. A. G. & Bochtis, D. (2011). Reducing the risk of soil compaction by applying "Jordværn Online"® when performing slurry distribution. Acta Agriculturae Scandinavica, Section B - Soil & Plant Science, 61(3), 209-213. https://doi.org/10.1080/09064710.2010.490535

Gheisarnejad Chirani, M., Akhbari, A., Rahimi, M., Andresen, B. & Khooban, M. H. (2022). Reducing Impact of Constant Power Loads on DC Energy Systems by Artificial Intelligence. IEEE Transactions on Circuits and Systems II: Express Briefs, 69(12), 4974-4978. Advance online publication. https://doi.org/10.1109/TCSII.2022.3194271

Mukherjee, M., Kumar, V., Kumar, S., Lloret, J., Zhang, Q. & Guo, M. (2021). Reconfigurable Intelligent Surface-assisted Edge Computing to Minimize Delay in Task Offloading. In 2021 IEEE Global Communications Conference (GLOBECOM) IEEE. https://doi.org/10.1109/GLOBECOM46510.2021.9685374

Li, N., Iosifidis, A. & Zhang, Q. (2022). Receptive Field-based Segmentation for Distributed CNN Inference Acceleration in Collaborative Edge Computing. In ICC 2022 - IEEE International Conference on Communications (pp. 4281-4286). IEEE. https://doi.org/10.1109/ICC45855.2022.9838547

Iqbal, S., Khan, T. M., Naveed, K., Naqvi, S. S. & Nawaz, S. J. (2022). Recent trends and advances in fundus image analysis: A review. Computers in Biology and Medicine, 151, Article 106277. https://doi.org/10.1016/j.compbiomed.2022.106277

Figueiredo, R. P. D., Sejersen, J. L. F., Hansen, J. G., Brandão, M. & Kayacan, E. (2021). Real-Time Volumetric-Semantic Exploration and Mapping: An Uncertainty-Aware Approach.

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. Advance online publication. https://doi.org/10.1002/rse2.245

Hervella, C., Diez, L., Fernández, F., Marcano, N. J. H., Jacobsen, R. H. & Agüero, R. (2022). Realistic Assessment of Transport Protocols Performance over LEO-based Communications. In PE-WASUN '22: Proceedings of the 19th ACM International Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor & Ubiquitous Networks (pp. 91-98). Association for Computing Machinery. https://doi.org/10.1145/3551663.3558680

Shi, L., Pantic, M., Andersson, O., Tognon, M., Siegwart, R. & Jacobsen, R. H. (2022). Reactive Motion Planning for Rope Manipulation and Collision Avoidance using Aerial Robots. In IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022 (pp. 3384-3391). IEEE. https://doi.org/10.1109/IROS47612.2022.9981658

Payne, D. N. R., Abbott, M. D., Claville Lopez, A., Zeng, Y., Hang Fung, T., R. McIntosh, K., Cruz-Campa, J., Davidsen, R. S., Plakhotnyuk, M. & Bagnall, D. M. (2017). Rapid optical modelling of plasma textured silicon. In Proceedings of the 33rd European Photovoltaic Solar Energy Conference and Exhibition (EUPVSEC)

Gheisarnejad Chirani, M. & Khooban, M. H. (2023). Quantum Power Electronics: From Theory to Implementation. arXiv. https://arxiv.org/abs/2303.04763

Faurby, C. F. D., Wang, Y., Paesani, S., Ruf, F., Volet, N., Heck, M., Wieck, A. D., Ludwig, A., Midolo, L. & Lodahl, P. (2023). Quantum-Dot Single-Photon Sources Processed on Silicon-Nitride Integrated Circuits. Paper presented at Conference on Laser and Electro-Optics (CLEO) , San Jose, California, United States.

Gheisarnejad Chirani, M. & Khooban, M. H. (2023). Quantum Deep Learning for Fast Switching of Full-Bridge Power Converters. Designs. https://www.mdpi.com/2411-9660/7/3/60

Johansen, P. (2004). Quantification of Cavitation in the Vicinity of Mechanical Heart Valves.

Rehman, N. U. & Mandic, D. P. (2009). Qualitative analysis of rotational modes within three dimensional empirical mode decomposition. In 2009 IEEE International Conference on Acoustics, Speech and Signal Processing IEEE. https://doi.org/10.1109/icassp.2009.4960367

Jensen, R. I. T. & Iosifidis, A. (2023). Qualifying and raising anti-money laundering alarms with deep learning. Expert Systems with Applications, 214, Article 119037. https://doi.org/10.1016/j.eswa.2022.119037

Rehman, N. U. & Mandic, D. P. (2010). Quadrivariate Empirical Mode Decomposition. In The 2010 International Joint Conference on Neural Networks (IJCNN) IEEE. https://doi.org/10.1109/ijcnn.2010.5596768

Hosseinzadeh, M., Wachal, A., Khamfroush, H. & Lucani Rötter, D. E. (2022). QoS-Aware Priority-Based Task Offloading for Deep Learning Services at the Edge. In 2022 IEEE Annual Consumer Communications & Networking Conference (CCNC) (pp. 319-325). IEEE. https://doi.org/10.1109/CCNC49033.2022.9700676

Hudson, N., Khamfroush, H. & Lucani Rötter, D. E. (2021). QoS-Aware Placement of Deep Learning Services on the Edge with Multiple Service Implementations. In 30th International Conference on Computer Communications and Networks, ICCCN 2021 IEEE. https://doi.org/10.1109/ICCCN52240.2021.9522156

Alizadeh, H., Koolivand, Y. & Sodagar, A. M. (2022). Pulse-Based, Multi-Beam Optical Link for Data Telemetry to Implantable Biomedical Microsystems. In 20th IEEE International Interregional NEWCAS Conference, NEWCAS 2022 - Proceedings (pp. 529-532). IEEE. https://doi.org/10.1109/NEWCAS52662.2022.9842007

Heidari, N. & Iosifidis, A. (2021). Progressive Spatio-Temporal Graph Convolutional Network for Skeleton-Based Human Action Recognition. In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (Vol. 2021-June, pp. 3220-3224). IEEE. https://doi.org/10.1109/ICASSP39728.2021.9413860

Heidari, N. & Iosifidis, A. (2021). Progressive Spatio-Temporal Bilinear Network with Monte Carlo Dropout for Landmark-based Facial Expression Recognition with Uncertainty Estimation. arXiv.org. https://arxiv.org/pdf/2106.04332.pdf

Heidari, N. & Iosifidis, A. (2021). Progressive Graph Convolutional Networks for Semi-Supervised Node Classification. IEEE Access, 9, 81957-81968. https://doi.org/10.1109/ACCESS.2021.3085905

Tran, D. T., Gabbouj, M. & Iosifidis, A. (2022). Progressive and compressive learning. In A. Iosifidis & A. Tefas (Eds.), Deep Learning for Robot Perception and Cognition (pp. 187-220). Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00014-2

Kakavandi, F., de Reus, R., Gomes, C., Heidari, N., Iosifidis, A. & Larsen, P. G. (2022). Product Quality Control in Assembly Machine under Data Restricted Settings. In 2022 IEEE 20th International Conference on Industrial Informatics, INDIN 2022 (pp. 735-741). IEEE. https://doi.org/10.1109/INDIN51773.2022.9976173

Macedo, H. D. & Pierce, K. (Eds.) (2022). Proceedings of the 20th International Overture Workshop. https://doi.org/10.48550/arXiv.2208.10233

Macedo, H. D., Thule, C. & Pierce, K. (2021). Proceedings of the 19th International Overture Workshop. https://arxiv.org/abs/2110.09371

Asplund, F., Macedo, H. D. & Sassanelli, C. (2021). Problematizing the Service Portfolio of Digital Innovation Hubs. In L. M. Camarinha-Matos, X. Boucher & H. Afsarmanesh (Eds.), Smart and Sustainable Collaborative Networks 4.0 - 22nd IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2021, Proceedings: 22nd IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2021, Saint-Étienne, France, November 22–24, 2021, Proceedings (pp. 433-440). Springer. https://doi.org/10.1007/978-3-030-85969-5_40

Larsen, E. L., Espelund, U., Lauritsen, S. M., Thiesson, B., Lange, J., Friis Kjeldsen, G. & Jørgensen, M. J. (2022). +Priokritisk. Early identification of clinical detorioriation among hospitalized patients by explainable AI. Poster session presented at Symposium on Artificial Intelligence for Learning Health Systems.

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

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, Article 120285. https://doi.org/10.1016/j.eswa.2023.120285

Shabani, M., Magris, M., Tzagkarakis, G., Kanniainen, J. & Iosifidis, A. (2023). Predicting the State of Synchronization of Financial Time Series using Cross Recurrence Plots. In Neural Computing and Applications (Vol. 35, pp. 18519–18531). Springer. https://doi.org/10.1007/s00521-023-08674-y

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Technical reports

Department of Electrical and Computer Engineering publishes technical reports covering our research areas.

With the reports, we wish to communicate the newest knowledge and research to society ahead of and during the publication process which can take up to a year.

Read the technical reports by following the link below:

Technical Report Department of Electrical and Computer Engineering

PhD dissertations

At the Department of Electrical and Computer Engineering, PhD dissertations are published via Aarhus University Library's/State and University Library's online E-books platform that is open access. You can find the published dissertations by following the link below.

PhD dissertations at Department of Electrical and Computer Engineering

AU Engineering Profile

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Get a copy of the AU Engineering Profile 2022

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