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

Sortér efter: Dato | Forfatter | Titel

Li, N., Iosifidis, A. & Zhang, Q. (2022). Receptive Field-based Segmentation for Distributed CNN Inference Acceleration in Collaborative Edge Computing. I ICC 2022 - IEEE International Conference on Communications (s. 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, Artikel 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. 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. I PE-WASUN '22: Proceedings of the 19th ACM International Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor & Ubiquitous Networks (s. 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. I IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022 (s. 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. I 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. Afhandling præsenteret på Conference on Laser and Electro-Optics (CLEO) , San Jose, California, USA.

Gheisarnejad Chirani, M. & Khooban, M. H. (2023). Quantum Deep Learning for Fast Switching of Full-Bridge Power Converters. Designs, 7(3), Artikel 60. https://doi.org/10.3390/designs7030060

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

Hallerstede, S. & Hoang, T. S. (2007). Qualitative probabilistic modelling in Event-B. I Integrated Formal Methods - 6th International Conference, IFM 2007, Proceedings (s. 293-312). Springer Verlag. https://doi.org/10.1007/978-3-540-73210-5_16

Rehman, N. U. & Mandic, D. P. (2009). Qualitative analysis of rotational modes within three dimensional empirical mode decomposition. I 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, Artikel 119037. https://doi.org/10.1016/j.eswa.2022.119037

Rehman, N. U. & Mandic, D. P. (2010). Quadrivariate Empirical Mode Decomposition. I 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. I 2022 IEEE Annual Consumer Communications & Networking Conference (CCNC) (s. 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. I 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. I 20th IEEE International Interregional NEWCAS Conference, NEWCAS 2022 - Proceedings (s. 529-532). IEEE. https://doi.org/10.1109/NEWCAS52662.2022.9842007

Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2023). PromptMix: Text-to-image diffusion models enhance the performance of lightweight networks. I 2023 International Joint Conference on Neural Networks (IJCNN)

Heidari, N. & Iosifidis, A. (2021). Progressive Spatio-Temporal Graph Convolutional Network for Skeleton-Based Human Action Recognition. I ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (Bind 2021-June, s. 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. I A. Iosifidis & A. Tefas (red.), Deep Learning for Robot Perception and Cognition (s. 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. I 2022 IEEE 20th International Conference on Industrial Informatics, INDIN 2022 (s. 735-741). IEEE. https://doi.org/10.1109/INDIN51773.2022.9976173

Macedo, H. D. & Pierce, K. (red.) (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. I L. M. Camarinha-Matos, X. Boucher & H. Afsarmanesh (red.), 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 (s. 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 præsenteret på 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

Hallerstede, S. & Kamburjan, E. (2023). Preface: Applications of Formal Methods and Digital Twins. CEUR Workshop Proceedings, 3507.

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, Artikel 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. I Neural Computing and Applications (Bind 35, s. 18519–18531). Springer. https://doi.org/10.1007/s00521-023-08674-y

Kragh, M. F., Rimestad, J., Lassen, J. T., Berntsen, J. & Karstoft, H. (2022). Predicting embryo viability based on self-supervised alignment of time-lapse videos. IEEE Transactions on Medical Imaging, 41(2), 465-475. https://doi.org/10.1109/TMI.2021.3116986

Peric, V. S. & Vanfretti, L. (2014). Power-system ambient-mode estimation considering spectral load properties. IEEE Transactions on Power Systems, 29(3), 1133-1143. Artikel 6683082. https://doi.org/10.1109/TPWRS.2013.2292331

Li, L., Looney, D., Park, C., Rehman, N. U. & Mandic, D. P. (2011). Power independent EMG based gesture recognition for robotics. I 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE. https://doi.org/10.1109/iembs.2011.6090036

Jeppesen, J. H., Nørremark, M. & Jacobsen, R. H. (2022). Potato Cyst Nematode Detection based on Open Satellite Data. Aarhus Universitet - DCA - Nationalt Center for Fødevarer og Jordbrug. Advisory report from DCA – National Center for Food and Agriculture

Schranz, T., Legaard, C. M., Tola, D. & Schweiger, G. (2021). Portable runtime environments for Python-based FMUs: Adding Docker support to UniFMU. I Proceedings of 14th Modelica Conference 2021 (s. 419-424) https://doi.org/10.3384/ecp21181419

Kamari, A., Petersen, J. H. & Schultz, C. P. L. (2021). Popularizing DGNB in the Danish construction industry: A field study of the industry via a qualitative comparative analysis. I Proceedings of the 38th International Conference of CIB W78, Luxembourg, 13-15 October: Joint Conference CIB W78 - LDAC 2021 (s. 638-649). Artikel 64. http://itc.scix.net/paper/w78-2021-paper-064

Henriksen, M. L., Karlsen, C. B., Klarskov, P. & Hinge, M. (2022). Plastic classification via in-line hyperspectral camera analysis and unsupervised machine learning. Vibrational Spectroscopy, 118, Artikel 103329. https://doi.org/10.1016/j.vibspec.2021.103329

Nørremark, M. (2022). Pilot project on precision farming. 4. Abstract fra Advances and Innovations in Agricultural Engineering., Herning, Danmark.

Zehtabiyan-Rezaie, N., Iosifidis, A. & Abkar, M. (2023). Physics-Guided Machine Learning for Wind-Farm Power Prediction: Toward Interpretability and Generalizability. PRX Energy, 2(1), Artikel 013009. https://doi.org/10.1103/PRXEnergy.2.013009

Rasmussen, S. M., Nielsen, T., Hody, S., Hager, H. & Schousboe, L. P. (2021). Photoplethysmography for demarcation of cutaneous squamous cell carcinoma. Scientific Reports, 11, Artikel 21467. https://doi.org/10.1038/s41598-021-00645-4

Benatto, G. A. D. R., Chi, M., B Jensen, O., Santamaria Lancia, A. A., Riedel-Lyngskær, N., Iandolo, B., Davidsen, R. S., Hansen, O., Thorsteinsson, S. & Behrensdorff Poulsen, P. (2018). Photoluminescence imaging induced by laser line scan: Study for outdoor field inspections. I 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) (s. 395-399) https://doi.org/10.1109/PVSC.2018.8547416

Mohapatra, A., Hamacher, T. & Peric, V. S. (2022). PHIL Infrastructure in CoSES Microgrid Laboratory. I Proceedings of 2022 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2022 IEEE. https://doi.org/10.1109/ISGT-Europe54678.2022.9960295

Cornejo, M., Mohapatra, A., Candas, S. & Peric, V. S. (2022). PHIL implementation of a decentralized online OPF for active distribution grids. I 2022 IEEE Power and Energy Society General Meeting, PESGM 2022 IEEE Computer Society. https://doi.org/10.1109/PESGM48719.2022.9916705

Jeppesen, J., Christensen, J., Johansen, P. & Beniczky, S. (2023). Personalized seizure detection using logistic regression machine learning based on wearable ECG-monitoring device. Seizure, 107, 155-161. https://doi.org/10.1016/j.seizure.2023.04.012

Mohammadi, S., Pahlevani, P. & Lucani, D. E. (2021). Perpetual Network Coding for Delay Sensitive Applications. Wireless Personal Communications, 120(2), 923-947. https://doi.org/10.1007/s11277-021-08497-x

Talasila, P. & Lucani Rötter, D. E. (2021). Performance of Generalized Deduplication Under Different Input Conditions. I European Wireless Conference: 26th European Wireless Conference IEEE. https://ieeexplore.ieee.org/document/9657095

Tran, D. T., Gabbouj, M. & Iosifidis, A. (2020). Performance Indicator in Multilinear Compressive Learning. I 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 (s. 1822-1828). Artikel 9308418 IEEE. https://doi.org/10.1109/SSCI47803.2020.9308418

Viser resultater 201 til 250 ud af 862

Forrige

Næste

Tekniske rapporter

Institut for Elektro- og Computerteknologi udgiver en serie af tekniske rapporter.

Formålet med rapporterne er at formidle aktuel viden til omverdenen forud for og under publiceringsprocessen, som i nogle tilfælde kan tage op til et år.

Læs de tekniske rapporter ved at klikke nedenfor:

Technical Report Department of Electrical and Computer Engineering

Ph.d.-afhandlinger

Ph.d.-afhandinger ved Institut for Elektro- og Computerteknologi udgives gennem Statsbibliotekets/AU library's online E-books platform, hvor der er open access. Du kan finde publicerede afhandlinger ved at følge linket nedenfor.

Ph.d.-afhandlinger ved Institut for Elektro- og Computerteknologi

AU Engineering Profile

Download AU Engineering Profile 2013-2022:

Få tilsendt AU Engineering Profile 2022

Ønsker du at modtage et eksemplar af AU Engineering Profile 2022, er du velkommen til at sende en mail til contact@auengineering.au.dk

Revideret 10.08.2023

AU Engineering