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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Jensen, F., Hassan, A. & Bazzi, A. (2022). A Comparison Between Nonlinear Kalman Filters for Sensorless Induction Motor Drives. Afhandling præsenteret på IEEE Energy Conversion Congress and Expo (ECCE 2022), Detroit, Michigan, USA. https://doi.org/10.1109/ECCE50734.2022.9947433

Jensen, A. L., Kristensen, E. F. & Grøn Sørensen, C. (2022). Feasibility study for organic farming. Poster session præsenteret på The XX CIGR World Congress 2022, Kyoto, Japan.

Jensen, J. C. S. (Producent) & Nørremark, M. (Producent). (2022). Influence of the tire pressure on yield: Fendt VarioGrip. Billeder, Video- og Lydoptagelser (digital) https://www.youtube.com/watch?v=i7pZQ41xzkI

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

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

Jensen, R. I. T., Ferwerda, J., Jørgensen, K. S., Jensen, E. R., Borg, M., Krogh, M. P., Jensen, J. B. & Iosifidis, A. (2023). A synthetic data set to benchmark anti-money laundering methods. Scientific Data, 10(1), Artikel 661. https://doi.org/10.1038/s41597-023-02569-2

Jensen, R. I. T. & Iosifidis, A. (2023). Fighting Money Laundering With Statistics and Machine Learning. IEEE Access, 8889-8903.

Jakobsen, M. O., Herskind, E. S., Pedersen, C. F. & Knudsen, M. B. (2023). Detecting insufficient lubrication in rolling bearings, using a low cost MEMS microphone to measure vibrations. Mechanical Systems and Signal Processing, 200, Artikel 110553. https://doi.org/10.1016/j.ymssp.2023.110553

Jakobsen, M. O. (2023). Detection of Lubrication Conditions in Ball Bearings Using Acoustic Ultrasound Signals.

Jacobsen, R. H. & Marandi, S. A. (2021). Security Threats Analysis of the Unmanned Aerial Vehicle System. I MILCOM 2021 - 2021 IEEE Military Communications Conference (s. 1-7) https://doi.org/10.1109/MILCOM52596.2021.9652900

Jacobsen, R. H., Matlekovic, L., Shi, L., Malle, N., Ayoub, N., Hageman, K., Hansen, S., Nyboe, F. F. & Ebeid, E. (2023). Design of an Autonomous Cooperative Drone Swarm for Inspections of Safety Critical Infrastructure. Applied Sciences (Switzerland), 13(3), Artikel 1256. https://doi.org/10.3390/app13031256

Iversen, M., Monisha, M. & Agarwala, S. (2022). Flexible, Wearable and Fully-printed Smart Patch for pH and Hydration Sensing in Wounds. International Journal of Bioprinting, 8(1), 41-49. https://doi.org/10.18063/IJB.V8I1.447

Islam, M. T., Khan, H. A., Naveed, K., Nauman, A., Gulfam, S. M. & Kim, S. W. (2023). LUVS-Net: A Lightweight U-Net Vessel Segmentor for Retinal Vasculature Detection in Fundus Images. Electronics, 12(8), Artikel 1786. https://doi.org/10.3390/electronics12081786

Iraji, M., Dehghani, M., Mohammadi, M., Vafamand, N. & Boudjadar, J. (2021). Motor Current Signature Analysis Using Shapelet. I H. Selvaraj, G. Chmaj & D. Zydek (red.), Proceedings of the 27th International Conference on Systems Engineering, ICSEng 2020 (s. 23-33). Springer. https://doi.org/10.1007/978-3-030-65796-3_3

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

Iqbal, S., Naveed, K., Naqvi, S. S., Naveed, A. & Khan, T. M. (2023). Robust retinal blood vessel segmentation using a patch-based statistical adaptive multi-scale line detector. Digital Signal Processing: A Review Journal, 139, Artikel 104075. https://doi.org/10.1016/j.dsp.2023.104075

Iosifidis, A. & Tefas, A. (2022). Introduction. I A. Iosifidis & A. Tefas (red.), Deep Learning for Robot Perception and Cognition Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00006-3

Inci, E. O., Croes, J., Desmet, W., Gomes, C., Thule, C., Lausdahl, K. & Larsen, P. G. (2021). The Effect and Selection of Solution Sequence in Co-Simulation. 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/ANNSIM52504.2021.9552130

Inci, E. O., Desmet, W., Gomes, C. & Croes, J. (2023). Error Estimators for Adaptive Scheduling Algorithm for Serial Co-Simulation. I M. J. Blas & G. Alvarez (red.), Proceedings of the 2023 Annual Modeling and Simulation Conference, ANNSIM 2023 (s. 73-83). Institute of Electrical and Electronics Engineers Inc..

Inceoglu, F., Hernandez Marcano, N. J., Jacobsen, R. H. & Karoff, C. (2020). A General Overview for Localizing Short Gamma-Ray Bursts with a CubeSat Mega-Constellation. Frontiers in Astronomy and Space Science, 7(November), Artikel 573060. https://doi.org/10.3389/fspas.2020.573060

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

Imanberdiyev, N., Sood, S., Kircali, D. & Kayacan, E. (2022). Design, development and experimental validation of a lightweight dual-arm aerial manipulator with a COG balancing mechanism. Mechatronics, 82, Artikel 102719. https://doi.org/10.1016/j.mechatronics.2021.102719

Ibrahim, I. A. F. A. H., Bochtis, D., Grøn Sørensen, C. & Nørremark, M. (2010). Automated generation of guidance lines for operational field planning. Biosystems Engineering, 107(4), 294-306. https://doi.org/10.1016/j.biosystemseng.2010.09.001

Ibanez, F., Alsadat, M., Vlasov, Y., Vorobev, P., Terzija, V., Pant, P. & Peric, V. (2022). Limiting transients for grid-forming inverters using a phase limiter. I 11th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2022 (s. 299-304). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICRERA55966.2022.9922719

Ibanez, F., Mahmoud, A. S., Yaroslav, V., Peric, V. & Vorobev, P. (2023). Improving the power sharing transients in droop-controlled inverters with the introduction of an angle difference limiter. International Journal of Electrical Power and Energy Systems, 153, Artikel 109371. https://doi.org/10.1016/j.ijepes.2023.109371

Iandolo, B., Sánchez Nery, A. P., Davidsen, R. S. & Hansen, O. (2019). Black silicon with ultra‐low surface recombination velocity fabricated by inductively coupled power plasma. Physica Status Solidi. Rapid Research Letters, 13(2). https://doi.org/10.1002/pssr.201800477

Iandolo, B., Davidsen, R. S. & Hansen, O. (2018). Avoiding blistering in Al2O3 deposited on planar and black Si. Solar Energy Materials & Solar Cells, 187, 23-29. https://doi.org/10.1016/j.solmat.2018.07.014

Hvilshøj, F., Iosifidis, A. & Assent, I. (2021). On Quantitative Evaluations of Counterfactuals.

Hvilshøj, F., Iosifidis, A. & Assent, I. (2021). ECINN: Efficient Counterfactuals from Invertible Neural Networks. I 32nd British Machine Vision Conference 2021, BMVC 2021, Virtual https://arxiv.org/abs/2103.13701

Huynh, H. A., Zamani, M., Ronchini, M., Farkhani, H. & Moradi, F. (2021). A 53GΩ@DC Input Impedance Multi-Channel Neural Recording Amplifier with 0.77 μvrms Input-Referred Noise for Deep Brain Implants. I 2021 IEEE Custom Integrated Circuits Conference, CICC 2021 - Proceedings Artikel 9431403 IEEE. https://doi.org/10.1109/CICC51472.2021.9431403

Hurst, A., Zhang, Q., Lucani Rötter, D. E. & Assent, I. (2021). Direct Analytics of Generalized Deduplication Compressed IoT Data. I 2021 IEEE Global Communications Conference, GLOBECOM 2021 - Proceedings IEEE. https://doi.org/10.1109/GLOBECOM46510.2021.9685589

Hurst, A., Lucani Rötter, D. E., Assent, I. & Zhang, Q. (2022). GLEAN: Generalized Deduplication Enabled Approximate Edge Analytics. IEEE Internet of Things Journal.

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

Hudert, M. M., Elvebakken, M. F., Meagher, M., Mangliar, L., Zhang, X. & Esterle, L. (2022). Deep learning enhanced robotic fabrication of timber-to-timber connections with densified hardwood nails. I Proceedings of the IASS 2022 Symposium affiliated with APCS 2022 conference: Innovation - Sustainability - Legacy (s. 1740-1748)

Høye, T. T., Dyrmann, M., Kjær, C., Nielsen, J., Bruus, M., Mielec, C. L., Vesterdal, M. S., Bjerge, K., Madsen, S. A., Jeppesen, M. R. & Melvad, C. (2022). Accurate image-based identification of macroinvertebrate specimens using deep learning — How much training data is needed? PeerJ, 10, Artikel e13837. https://doi.org/10.7717/peerj.13837

Hosseinzadeh, M., Wachal, A., Khamfroush, H. & Lucani Rötter, D. E. (2021). Optimal Accuracy-Time Trade-off For Deep Learning Services in Edge Computing Systems. I ICC 2021 - IEEE International Conference on Communications, Proceedings IEEE. https://doi.org/10.1109/ICC42927.2021.9500744

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

Hosseinzadeh, M., Hudson, N., Zhao, X., Khamfroush, H. & Lucani Rötter, D. E. (2021). Joint Compression and Offloading Decisions for Deep Learning Services in 3-Tier Edge Systems. I 2021 IEEE International Symposium on Dynamic Spectrum Access Networks, DySPAN 2021 (s. 254-261). IEEE. https://doi.org/10.1109/DySPAN53946.2021.9677398

Hosseini, S., Laursen, K., Rashidi, A., Mondal, T., Corbett, B. & Moradi, F. (2021). S-MRUT: Sectored-Multi Ring Ultrasonic Transducer for Selective Powering of Brain Implants. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 68(1), 191-200. Artikel 9112273. https://doi.org/10.1109/TUFFC.2020.3001084

Honoré, J. T., Rask, R. D. & Wagner, S. R. (2023). Fall Detection Combining Android Accelerometer and Step Counting Virtual Sensors. I G. A. Papadopoulos, A. Achilleos, E. Pissaloux & R. Velázquez (red.), ICT for Health, Accessibility and Wellbeing - 2nd International Conference, IHAW 2022, Revised Selected Papers (s. 3-16). Springer. https://doi.org/10.1007/978-3-031-29548-5_1

Homayounzade, M., Homayounzadeh, M. & Khooban, M. H. (2023). Robust positive control of tumour growth using angiogenic inhibition. IET Systems Biology, 17(5), 288-301. https://doi.org/10.1049/syb2.12076

Hjelseth, E. & Li, B. (2021). Use of “Reasoner” for automated building code compliance assessment. I Proceedings of the 38th International Conference of CIB W78 (s. 138-147) https://itc.scix.net/pdfs/w78-2021-paper-014.pdf

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

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

Henriksen, M. L., Pedersen, W. N., Klarskov, P. & Hinge, M. (2022). One step calibration of industrial hyperspectral cameras. Chemometrics and Intelligent Laboratory Systems, 227, Artikel 104609. https://doi.org/10.1016/j.chemolab.2022.104609

Hemakom, A., Ahrabian, A., Looney, D., Rehman, N. U. & Mandic, D. P. (2015). Nonuniformly sampled trivariate empirical mode decomposition. I 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) IEEE. https://doi.org/10.1109/icassp.2015.7178660

Helmstedt, C., Manouselis , N. M., Martín-Moncunill, D., Protonotarios, V., Sicilia, M-A., M. Stracke, C., Adamides, G., Aventurier, P., Belsis, P., Beyer, J., Biniari, K., Bouza, D., Ciotoli, F., Engel-Vermette, S., Nicola Ghirad, N. G., Koutoumanos, A., Jensen, A. L., Le Henaff, D., Masselin-Silvin , S. ... Tsiflidou, E. (2020). Opening Up Access to Scientific Information: Recommendations for Improving Virtual Repositories and Online Communities. University Publisher. https://hal.inrae.fr/hal-02806629/document

Heidary, J., Gheisarnejad Chirani, M., Rastegar, H. & Khooban, M. H. (2022). Survey on microgrids frequency regulation: Modeling and control systems. Electric Power Systems Research, 213, Artikel 108719. https://doi.org/10.1016/j.epsr.2022.108719

Heidary, J., Gheisarnejad Chirani, M. & Khooban, M. H. (2023). Stability Enhancement and Energy Management of AC-DC Microgrid based on Active Disturbance Rejection Control. Electric Power Systems Research, 217, Artikel 109105. https://doi.org/10.1016/j.epsr.2022.109105

Heidary, J., Oshnoei, S., Gheisarnejad Chirani, M., Khalghani, M. R. & Khooban, M. H. (2023). Shipboard Microgrid Frequency Control Based on Machine Learning Under Hybrid Cyberattacks. IEEE Transactions on Industrial Electronics, 1-11. https://ieeexplore.ieee.org/document/10232899

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