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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Ferrarini, B., Ehsan, S., Rehman, N. U., Leonardis, A. & McDonald-Maier, K. D. (2016). Automatic Selection of the Optimal Local Feature Detector. I Lecture Notes in Computer Science (s. 284-289). Springer International Publishing. https://doi.org/10.1007/978-3-319-41501-7_32

Fernández Khatiboun, D., Sadeghi, M., Rezaeiyan, Y. & Moradi, F. (2023). Digital Hardware Implementation of ReSuMe Learning Algorithm for Spiking Neural Networks. IEEE EMBC 2023.

Feng, H., Gomes, C., Thule, C., Lausdahl, K., Sandberg, M. & Larsen, P. G. (2021). The Incubator Case Study for Digital Twin Engineering. ArXiv. https://arxiv.org/pdf/2102.10390.pdf

Feng, H., Gomes, C., Thule, C., Lausdahl, K., Iosifidis, A. & Larsen, P. G. (2021). Introduction to Digital Twin Engineering. I C. R. Martin, M. J. Blas & A. I. Psijas (red.), 2021 Annual Modeling and Simulation Conference (ANNSIM) (s. 1-12). IEEE. https://doi.org/10.23919/ANNSIM52504.2021.9552135

Feng, H., Gomes, C., Iosifidis, A. & Larsen, P. G. (2021). Model-based monitoring and state estimation for digital twins: The Kalman filter. I C. R. Martin, M. J. Blas & A. I. Psijas (red.), Annual Modeling and Simulation Conference (ANNSIM 2021) (s. 1-2)

Feng, H., Gomes, C., Gil Arboleda, S., Mikkelsen, P. H., Tola, D., Larsen, P. G. & Sandberg, M. (2022). Integration Of The Mape-K Loop In Digital Twins. I C. R. Martin, N. Emami, M. J. Blas & R. Rezaee (red.), Proceedings of the 2022 Annual Modeling and Simulation Conference, ANNSIM (s. 102-113). IEEE. https://doi.org/10.23919/ANNSIM55834.2022.9859489

Feng, H. (2023). Digital Twin Engineering with an Application to an Incubator. Aarhus Universitet.

Feng, H., Gomes, C., Sandberg, M., Thule, C., Lausdahl, K. & Larsen, P. G. (2021). Developing a Physical and Digital Twin: An Example Process Model. I Companion Proceedings - 24th International Conference on Model-Driven Engineering Languages and Systems, MODELS-C 2021 (s. 286-295). IEEE. https://doi.org/10.1109/MODELS-C53483.2021.00050

Feng, H., Gomes, C., Sandberg, M., Macedo, H. D. & Larsen, P. G. (2022). Under What Conditions Does a Digital Shadow Track a Periodic Linear Physical System? I A. Cerone, M. Autili, A. Bucaioni, C. Gomes, P. Graziani, M. Palmieri, M. Temperini & G. Venture (red.), Software Engineering and Formal Methods. SEFM 2021 Collocated Workshops - CIFMA, CoSim-CPS, OpenCERT, ASYDE, Revised Selected Papers (s. 143-155). Springer. https://doi.org/10.1007/978-3-031-12429-7_11

Fehér, M., Yazdani, N., Hansen, M. T., Vester, F. E. & Lucani Rötter, D. E. (2020). Smart Meter Data Compression using Generalized Deduplication. I 2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings: Proceedings Artikel 9322393 IEEE. https://doi.org/10.1109/GLOBECOM42002.2020.9322393

Fehér, M., Yazdani, N., Aranha, D. F., Lucani Rötter, D. E., Hansen, M. T. & Vester, F. E. (2020). Side Channel Security of Smart Meter Data Compression Techniques. I 2020 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2020: Proceedings Artikel 9302931 IEEE. https://doi.org/10.1109/SmartGridComm47815.2020.9302931

Fehér, M., Lucani Rötter, D. E., Hansen, M. T. & Vester, F. E. (2021). Exploiting DLMS/COSEM Data Compression To Learn Power Consumption Patterns. I 2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2021 (s. 346-351). IEEE. https://doi.org/10.1109/SmartGridComm51999.2021.9632291

Fehér, M., Lucani Rötter, D. E., Hansen, M. T. & Vester, F. E. (2022). Stream Compression of DLMS Smart Meter Readings. I ICC 2022 - IEEE International Conference on Communications (s. 5517-5522). IEEE. https://doi.org/10.1109/ICC45855.2022.9838758

Fehér, M. (2023). On Compression for the Complete IoT Data Lifecycle: From Collection to Analytics. Aarhus Universitet.

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.

Fathollahidehkordi, A., Derakhshandeh, S. Y., Ghiasian, A. & Khooban, M. H. (2022). Utilization of dynamic wireless power transfer technology in multi-depot, multi-product delivery supply chain. Sustainable Energy, Grids and Networks, 32, Artikel 100836. https://doi.org/10.1016/j.segan.2022.100836

Fathollahidehkordi, A., Gheisarnejad Chirani, M., Boudjadar, J., Homayounzadeh, M. & Khooban, M. H. (2023). Optimal Design of Wireless Charging Electric Buses-Based Machine Learning: A Case Study of Nguyen-Dupuis Network. I E E E Transactions on Vehicular Technology, 72(7), 8449-8458. https://doi.org/10.1109/TVT.2023.3247838

Fathollahidehkordi, A., Gheisarnejad Chirani, M., Andresen, B., Farsizadeh, H. & Khooban, M. H. (2023). Robust Artificial intelligence Controller for Stabilization of Full-Bridge Converters Feeding Constant Power Loads. I E E E Transactions on Circuits and Systems. Part 2: Express Briefs, 70(9), 3504-3508. https://doi.org/10.1109/TCSII.2023.3270751

Fathollahidehkordi, A., Gheisarnejad Chirani, M., Boudjadar, J., Derakhshandeh, S. Y. & Khooban, M. H. (2023). Multi-Criteria Design of Electric Transit Bus Based on Wireless Charging Infrastructure: A Case Study of Real Road Map in Wakefield. Automation , 4(3). https://doi.org/10.3390/automation4030017

Fathollahidehkordi, A., Kargar, A. & Derakhshandeh, S. Y. (2022). Enhancement of power system transient stability and voltage regulation performance with decentralized synergetic TCSC controller. International Journal of Electrical Power & Energy Systems, 135, 107533. https://doi.org/10.1016/j.ijepes.2021.107533

Fathollahidehkordi, A., Derakhshandeh, S. Y., Ghiasian, A. & Masoum, M. AS. (2022). Optimal siting and sizing of wireless EV charging infrastructures considering traffic network and power distribution system. IEEE Access, 10, 117105-117117. https://doi.org/10.1109/ACCESS.2022.3219055

Fathollahidehkordi, A. & Andresen, B. (2023). Multi-Machine Power System Transient Stability Enhancement Utilizing a Fractional Order-Based Nonlinear Stabilizer. Fractal Fractional, 808. https://doi.org/10.3390/fractalfract7110808

Farooq, W., Islam, S. U., Khan, M. A., Rehman, S., Gulzari, U. A. & Boudjadar, J. (2022). UGAVs-MDVR: A Cluster-Based Multicast Routing Protocol for Unmanned Ground and Aerial Vehicles Communication in VANET. Applied Sciences, 12(23), Artikel 11995. https://doi.org/10.3390/app122311995

Farkhani, S., Skovsen, S. K., Dyrmann, M., Nyholm Jørgensen, R. & Karstoft, H. (2021). Weed classification using explainable multi-resolution slot attention. Sensors, 21(20), Artikel 6705. https://doi.org/10.3390/s21206705

Farkhani, S. (2022). Soft Regression based on Sparse Unbalanced Labels. Aarhus Universitet.

Fares, H., Ronchini, M., Zamani, M., Farkhani, H. & Moradi, F. (2022). In the realm of hybrid Brain: Human Brain and AI. ArXiv. https://doi.org/10.48550/arXiv.2210.01461

Far Brusatori, M. & Volet, N. (2022). External optical feedback engineered to reduce and stabilize the linewidth of diode lasers. I V. S. Ilchenko, A. M. Armani & J. V. Sheldakova (red.), Laser Resonators, Microresonators, and Beam Control XXIV Artikel 119870D SPIE - International Society for Optical Engineering. https://doi.org/10.1117/12.2609616

Far Brusatori, M., Klein, H. & Volet, N. (2023). Achieving High Stability of Dual-Wavelength U-Shaped Laser in the C-Band Using Optical Feedback. IEEE Photonics Technology Letters, 35(10), 573-576. https://doi.org/10.1109/lpt.2023.3264160

Far Brusatori, M., Klein, H. & Volet, N. (2022). Dual-wavelength laser in the C-band with narrow-linewidth reduced by optical feedback. Abstract fra IEEE Photonics Conference 2022. https://doi.org/10.1109/IPC53466.2022.9975567

Far Brusatori, M. (2023). Engineering Optical Feedback for Stable Diode Laser Performance. Aarhus University.

Faraji, B., Gheisarnejad, M., Rouhollahi, K., Esfahani, Z. & Khooban, M. H. (2021). Machine Learning Approach based on Ultra-Local Model Control for Treating Cancer Pain. I E E E Sensors Journal, 21(6), 8245-8252. Artikel 9285309. https://doi.org/10.1109/JSEN.2020.3042937

Faraji, B., Gheisarnejad, M., Yalsavar, M. & Khooban, M. H. (2021). An Adaptive ADRC Control for Parkinson’s Patients Using Machine Learning. IEEE Sensors Journal, 21(6), 8670 - 8678. Artikel 9311650. https://doi.org/10.1109/JSEN.2020.3048588

Faraji, B., Gheisarnejad, M., Esfahani, Z. & Khooban, M. H. (2022). Smart Sensor Control for Rehabilitation in Parkinson's Patients. IEEE Transactions on Emerging Topics in Computational Intelligence, 6(2), 267-275. https://doi.org/10.1109/TETCI.2020.3045483

Falay, B., Wilfling, S., Alfalouji, Q., Exenberger, J., Schranz, T., Legaard, C. M., Leusbrock, I. & Schweiger, G. (2021). Coupling physical and machine learning models: case study of a single-family house. I Proceedings of 14th Modelica Conference 2021 (s. 335-341) https://doi.org/10.3384/ecp21181335

Esterle, L., Gomes, C., Frasheri, M., Ejersbo, H., Tomforde, S. & Larsen, P. G. (2021). Digital twins for collaboration and self-integration. I Proceedings - 2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion, ACSOS-C 2021 (s. 172-177). IEEE. https://doi.org/10.1109/ACSOS-C52956.2021.00040

Esterle, L. (2022). Deep learning in multiagent systems. I A. Iosifidis & A. Tefas (red.), Deep Learning for Robot Perception and Cognition (s. 435-460). Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00022-1

Esterle, L. & King, D. W. (2021). Loosening Control—A Hybrid Approach to Controlling Heterogeneous Swarms. ACM Transactions on Autonomous and Adaptive Systems, 16(2), Artikel 5. https://doi.org/10.1145/3502725

Esterle, L., Ejersbo, H., Frasheri, M., Gomes, C., Macedo, H. D. & Larsen, P. G. (2022). Digital Twins for Autonomous Intelligent Systems: From Development to Deployment. I Proceedings - 2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion, ACSOS-C 2022 (s. 53-54). IEEE. https://doi.org/10.1109/ACSOSC56246.2022.00028

Esmaeili, M., Anvari-Moghaddam, A., Muyeen, S. M. & Peric, V. S. (2022). On the Role of Renewable Energy Policies and Electric Vehicle Deployment Incentives for a Greener Sector Coupling. IEEE Access, 10, 53873-53893. https://doi.org/10.1109/ACCESS.2022.3176012

Esfahani, Z. (2023). Copper-Based Redox Flow Batteries for Frequency Containment Reservation (FCR) Provision.

Eriksen, T. & Rehman, N. U. (2023). Data-driven nonstationary signal decomposition approaches: a comparative analysis. Scientific Reports, 13(1), Artikel 1798. https://doi.org/10.1038/s41598-023-28390-w

Ehsan, S., Clark, A., Leonardis, A., Rehman, N. U., Khaliq, A., Fasli, M. & McDonald-Maier, K. (2016). A Generic Framework for Assessing the Performance Bounds of Image Feature Detectors. Remote Sensing, 8(11), 928. https://doi.org/10.3390/rs8110928

Ehsan, S., Clark, A., Rehman, N. & McDonald-Maier, K. (2015). Integral Images: Efficient Algorithms for Their Computation and Storage in Resource-Constrained Embedded Vision Systems. Sensors, 15(7), 16804-16830. https://doi.org/10.3390/s150716804

Ehlers, M. H., Finger, R., El Benni, N., Gocht, A., Sørensen, C. A. G., Gusset, M., Pfeifer, C., Poppe, K., Regan, Á., Rose, D. C., Wolfert, S. & Huber, R. (2022). Scenarios for European agricultural policymaking in the era of digitalisation. Agricultural Systems, 196, Artikel 103318. https://doi.org/10.1016/j.agsy.2021.103318

Ebeid, E. S. M., Jacobsen, R. H., Schenider-Kamp, P., Vom Bögel, G., Guzzini, P., Luminari, N., Casarotti, C., Mandirola, M., Taurino, D. & Del Sole, A. (2022). Autonomous Drones to Ensure Safety in Transport: Concept and Implementations. 1-9. Afhandling præsenteret på SESAR Innovation days 2022, Budapest, Hungary, Ungarn.

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

Dybro, N., M. Allen, C., Grift, T., Grøn Sørensen, C. & C. Hansen, A. (2021). Sources of Increased Food Demand by 2050 and Options to Address the Challenge. Poster session præsenteret på ASABE.

Dormann, F., Frisk, O., Andersen, L. N. & Pedersen, C. F. (2021). Not All Noise Is Accounted Equally: How Differentially Private Learning Benefits From Large Sampling Rates. I 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing, MLSP 2021 IEEE. https://doi.org/10.1109/MLSP52302.2021.9596307

Dong, Z., Li, N., Iosifidis, A. & Zhang, Q. (2022). Design and Prototyping Distributed CNN Inference Acceleration in Edge Computing. ArXiv. https://doi.org/10.48550/arXiv.2211.13778

Dobbs, A. M., Ginn, D., Skovsen, S. K., Bagavathiannan, M. V., Mirsky, S. B., Reberg-Horton, C. S. & Leon, R. G. (2022). New directions in weed management and research using 3D imaging. Weed Science, 70(6), 641-647. https://doi.org/10.1017/wsc.2022.56

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