Publications by Signal Processing & Machine Learning

Are you looking for publications by Section of Signal Processing & Machine Learning? On this page you can find all the publications made by the Section of Signal Processing & Machine Learning - Department of Electrical and Computer Engineering, Aarhus University.

Below you can find a list of all the publications, their publishing date, their author(s), and titles. The list can be sorted by date, author, and title:

List of Publications

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Gaikwad, N., Liu, L., Griffiths, M. P., Vang, M. Ø., Grombacher, D. & Larsen, J. J. (2022). Thermal Model of the Apsu Transmitter for Lightweight and Compact Heat Sink Design. 11-13. Abstract fra The 8th International Workshop on Magnetic Resonance Sounding, Strasbourg, Frankrig. https://mrs2021.sciencesconf.org/data/pages/proceedings_MRS2021_distrib_v2.pdf

Hansen, P. M. & Jørgensen, R. (2001). The Risø Cropassessor - An idea to a low-cost, robust, simple and modular measuring device based on existing technology for monitoring the spatial field crop variation. I Grenier, G. & Blackmore, S. (eds.), Agro Montpellier, Montpellier, France (s. 37-42)

Jørgensen, R., Sørensen, C. A. G., Jacobsen, H., Kirk, K., Andersen, H. J. & Nantt, D. (2005). The potential of using robotics for data acquisition from multiple sensors within agricultural research. I Intelligent Systems in Design and Manufacturing VI. Proc. of SPIE Vol. 5999, 82-93. http://www.spiedl.org/

Christensen, S., Wu, O., Butcher, K., Hjort, N., Karstoft, H., Davis, S. & Østergaard, L. (2006). The Physiological Significance of the Tmax Parameter in Bolus Tracking MRI. Abstract fra ISMRM 14th Annual Meeting, Seattle, USA.

Mortensen, A. K., Skovsen, S., Karstoft, H. & Gislum, R. (2019). The Oil Radish Growth Dataset for Semantic Segmentation and Yield Estimation. Poster session præsenteret på IEEE Conference on Computer Vision and Pattern Recognition 2019, Long Beach, California, USA.

Mortensen, A. K., Skovsen, S., Karstoft, H. & Gislum, R. (2019). The Oil Radish Growth Dataset for Semantic Segmentation and Yield Estimation. I Proceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019 (s. 2703-2710). Artikel 9025602 IEEE. https://doi.org/10.1109/CVPRW.2019.00328

Mortensen, A. K., Skovsen, S., Karstoft, H. & Gislum, R. (2019). The Oil Radish Growth Dataset. Datasæt

Iosifidis, A., Marami, E., Tefas, A., Pitas, I. & Lyroudia, K. (2015). The MOBISERV-AIIA Eating and Drinking multi-view database for vision-based assisted living. Journal of Information Hiding and Multimedia Signal Processing, 6(2), 254-273. http://bit.kuas.edu.tw/~jihmsp/2015/vol6/JIH-MSP-2015-02-008.pdf

Skovsen, S., Dyrmann, M., Mortensen, A. K., Laursen, M. S., Gislum, R., Eriksen, J., Farkhani, S., Karstoft, H. & Nyholm Jørgensen, R. (2019). The GrassClover Image Dataset for Semantic and Hierarchical Species Understanding in Agriculture. Poster session præsenteret på IEEE Conference on Computer Vision and Pattern Recognition 2019, Long Beach, California, USA.

Skovsen, S., Dyrmann, M., Mortensen, A. K., Laursen, M. S., Gislum, R., Eriksen, J., Farkhani, S., Karstoft, H. & Nyholm Jørgensen, R. (2019). The GrassClover Image Dataset for Semantic and Hierarchical Species Understanding in Agriculture. I The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops IEEE. http://openaccess.thecvf.com/content_CVPRW_2019/html/CVPPP/Skovsen_The_GrassClover_Image_Dataset_for_Semantic_and_Hierarchical_Species_Understanding_CVPRW_2019_paper.html

Jørgensen, R. & Jørgensen, B. J. (1996). The effect of N2O emission on the net CO2-displacement by energy crop production. I Chartier, P., Ferrero, G. L., Henius, U.M., Hultbeg, S., Sachau, J. & Wiinblad, M. (eds.), Biomass for energy and the environment. Proc. 9th Europ. bioenergy conf., Copenhagen, Denmark. Vol. 3 (s. 1701-1706)

Ärje, J., Kärkkäinen, S., Meissner, K., Iosifidis, A., Ince, T., Gabbouj, M. & Kiranyaz, S. (2017). The effect of automated taxa identification errors on biological indices. Expert Systems with Applications, 72, 108-120. https://doi.org/10.1016/j.eswa.2016.12.015

Steen, K. A. & Karstoft, H. (2014). The acoustic adaptive frightening device-framework and algorithms. I 2014 IEEE Global Conference on Signal and Information Processing : GlobalSIP 2014 (s. 1117-1121). IEEE. https://doi.org/10.1109/GlobalSIP.2014.7032295

Sommer, W. L. & Iosifidis, A. (2020). Text-To-Image Synthesis Method Evaluation Based on Visual Patterns. I 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings (s. 4097-4101). Artikel 9053034 IEEE. https://doi.org/10.1109/ICASSP40776.2020.9053034

Tran, D. T., Magris, M., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2018). Tensor representation in high-frequency financial data for price change prediction. I 2017 IEEE Symposium Series on Computational Intelligence: SSCI 2017 - Proceedings (Bind 2017, s. 1-7). IEEE. https://doi.org/10.1109/SSCI.2017.8280812

Passalis, N., Tefas, A., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2020). Temporal logistic neural Bag-of-Features for financial time series forecasting leveraging limit order book data. Pattern Recognition Letters, 136, 183-189. https://doi.org/10.1016/j.patrec.2020.06.006

Passalis, N., Tefas, A., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2020). Temporal Bag-of-Features Learning for Predicting Mid Price Movements using High Frequency Limit Order Book Data. IEEE Transactions on Emerging Topics in Computational Intelligence, 4(6), 774-785. https://doi.org/10.1109/TETCI.2018.2872598

Heidari, N. & Iosifidis, A. (2020). Temporal Attention-Augmented Graph Convolutional Network for Efficient Skeleton-Based Human Action Recognition. I Proceedings of ICPR 2020 - 25th International Conference on Pattern Recognition (s. 7907-7914). Artikel 9412091 IEEE. https://doi.org/10.1109/ICPR48806.2021.9412091

Tran, D. T., Iosifidis, A., Kanniainen, J. & Gabbouj, M. (2019). Temporal Attention-Augmented Bilinear Network for Financial Time-Series Data Analysis. IEEE Transactions on Neural Networks and Learning Systems, 30(5), 1407 - 1418 . https://doi.org/10.1109/TNNLS.2018.2869225

Hejlesen, O. K., Larsen, L. B. & Pedersen, C. F. (2006). Telemedicine supported patient-centred diabetes care. I Proceedings 4th Scandinavian Conference on Health Informatics, SHI2006, 24-25 August 2006, Aalborg, Denmark

Nyholm Jørgensen, R., Laursen, M. S. & Therkildsen, O. R., (2018). Teknologier til understøttelse af vildtvenlig høst med henblik på at reducere høstdrab samt skader på fugle og pattedyr, Nr. Journal 2017-760-000470, 9 s., mar. 07, 2018.

Nyholm Jørgensen, R., Laursen, M. S. & Therkildsen, O. R., (2018). Tekniske metoder til at detektere fugle og reder og reducere risiko for at de dræbes eller skades ved høst, Nr. 2018-760-000730, 3 s., maj 14, 2018.

Vang, M., Grombacher, D., Griffiths, M. P., Liu, L. & Larsen, J. J. (2023). Technical note: High-density mapping of regional groundwater tables with steady-state surface nuclear magnetic resonance - three Danish case studies. Hydrology and Earth System Sciences, 27(16), 3115-3124. https://doi.org/10.5194/hess-27-3115-2023

Pedersen, C. F. (2013). Teaching Portfolio. Section of Electrical and Computer Engineering, Department of Engineering, Aarhus University, DK.

Thanh Nguyen, T., Kayacan, E., G. de Baerdemaeker, J. & Saeys, W. (2013). Task and Motion Planning for Apple-Harvesting Robot. I IFAC Proceedings Volumes (18 udg., Bind 46, s. 247-252). Elsevier. https://doi.org/10.3182/20130828-2-SF-3019.00063

Bækkegaard, S., Blixenkrone-Møller, J., Larsen, J. J. & Jochumsen, L. (2018). Target Classiﬁcation Using Kinematic Data and a Recurrent Neural Network. I H. Rohling (red.), 2018 19th International Radar Symposium, IRS 2018: Proceedings (Bind 2018). Artikel 8448118 IEEE. https://doi.org/10.23919/IRS.2018.8448118

Kryger, P. & Bjerge, K. (2019). Tælling af varroamider. I Varroatolerance i Danmark : de første skridt februar 2019 (s. 28-31). Danmarks Biavlerforening.

Frasheri, M., Katsaros, P., Iosifidis, A., Hansen, S. T., Gomes, C., Evans, V. T. & Larsen, P. G. (2024). System Monitoring through a Digital Twin. I J. Fitzgerald, C. Gomes & P. G. Larsen (red.), The Engineering of Digital Twins (s. 189-207). Springer. https://doi.org/10.1007/978-3-031-66719-0_9

Green, O. & Jørgensen, R. (2007). System for implement draft reduction: Patent anmeldt 6. februar 2007. (Patentnummer DK2008/050026).

Jørgensen, R. N. & Green, O. (2008). System for implement draft reduction. (Patentnummer WO2008095503). http://wo.espacenet.com/publicationDetails/biblio?CC=WO&NR=2008095503A1&KC=A1&DB=wo.espacenet.com&locale=en_EP

Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2024). Synthetic studies to investigate the ability of steady-state surface NMR to resolve T2. I NSG 2024 30th European Meeting of Environmental and Engineering Geophysics (s. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420092

Siboska, D., Karstoft, H. & Pedersen, H. (2014). Synchronization of Electroencephalography and Eye Tracking using Global Illumination Changes. I Biosignals 2014 - 7th International Conference on Bio-inspired Systems and Signal Processing (s. 55-60). SCITEPRESS Digital Library. https://doi.org/10.5220/0004800400550060

Hein, A., Larsen, J. J. & D. Parsekian, A. (2017). Symmetry based frequency domain processing to remove harmonic noise from surface nuclear magnetic resonance measurements. Geophysical Journal International, 208(2), 724-736. https://doi.org/10.1093/gji/ggw433

Iosifidis, A. (2010, mar.). Surveillance of moving target using a mechatronic system with active camera.

Larsen, J. J., Kass, A., Grombacher, D. & Griffiths, M. P. (2024). Surface NMR with Very Long Transmitter Pulses. Abstract fra AGU Fall meeting 2024, Washington DC, USA.

Larsen, J. J. & Behroozmand, A. A. (2015). Surface-NMR in High Noise Areas. Poster session præsenteret på The 21st European Meeting of Environmental and Engineering Geophysics, Turin, Italien.

Larsen, J. J., Pedersen, S. S., Foged, N. & Auken, E. (2021). Suppression of very low frequency radio noise in transient electromagnetic data with semi-tapered gates. Geoscientific Instrumentation, Methods and Data Systems, 10(1), 81-90. Artikel 8. https://doi.org/10.5194/gi-10-81-2021

Mygdalis, V., Iosifidis, A., Tefas, A. & Pitas, I. (2014). Supervised video summarization by content-based video segment selection. I European Conference on Visual Media Production (CVMP) University of Bristol. https://core.ac.uk/download/pdf/73983041.pdf

Iosifidis, A. & Gabbouj, M. (2016). Supervised Subspace Learning based on Deep Randomized Networks. I 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings (s. 2584-2588). Artikel 7472144 IEEE. https://doi.org/10.1109/ICASSP.2016.7472144

Hedegaard Morsing, L., Sheikh-Omar, O. A. & Iosifidis, A. (2021). Supervised Domain Adaptation using Graph Embedding. Afhandling præsenteret på 25th International Conference on Pattern Recognition, Milan, Italien. https://arxiv.org/abs/2003.04063

Hedegaard Morsing, L., Sheikh-Omar, O. A. & Iosifidis, A. (2021). Supervised Domain Adaptation: A Graph Embedding Perspective and a Rectified Experimental Protocol. IEEE Transactions on Image Processing, 30, 8619-8631. https://doi.org/10.1109/TIP.2021.3118978

Sohrab, F., Raitoharju, J., Gabbouj, M. & Iosifidis, A. (2018). Subspace Support Vector Data Description. I 2018 24th International Conference on Pattern Recognition, ICPR 2018: ICPR 2018 (Bind 2018, s. 722-727). Artikel 8545819 IEEE. https://doi.org/10.1109/ICPR.2018.8545819

Iosifidis, A. (2008, jun.). Subcritical nuclear reactor operation – Accelerator Driven System (ADS).

Schiopu, I., Gabbouj, M., Iosifidis, A., Zeng, B. & Liu, S. (2017). Subaperture Image Segmentation for Lossless Compression. I The seventh International Conference on Image Processing Theory, Tools and Applications http://www.cs.tut.fi/~iosifidi/files/conference/2017_IPTA_SAIC.pdf?dl=0

Jørgensen, R. (2002). Study on Line Imaging Spectroscopy as a Tool for Nitrogen Diagnostics in Precision Farming.

Sridharan, K. S., Johnsen, E. L., Beniczky, S., Johansen, L. G., Sunde, N. & Østergaard, K. (2015). Studying somatosensory function in Parkinson’s disease using Magnetoencephalography. Poster session præsenteret på PhD day 2015, Aarhus University, Danmark.

Zullo, H., Cline, K., Parker, M., Buckmire, R., George, J., Gurski, K., Larsen, J. J., Mellor, B. & Oberweiser, J. (2011). Student Surveys: What Do They Think? I K. Cline & H. Zullo (red.), Teaching Mathematics with Classroom Voting, With and Without Clicker (s. 29-34). Mathematical Association of America. http://www.maa.org/publications/ebooks/teaching-mathematics-with-classroom-voting-with-and-without-clickers

Hedegaard Morsing, L., Alok, A., Jose, J. & Iosifidis, A. (2022). Structured Pruning Adapters. https://doi.org/10.48550/arXiv.2211.10155

Christensen, S., Søgaard, H. T., Kudsk, P., Nørremark, M., Lund, I., Shahrak Nadimi, E. & Jørgensen, R. N. (2009). Site Specific Weed Control Technologies. Weed Research, 49(3), 225-232. https://doi.org/10.1111/j.1365-3180.2009.00694.x

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Revideret 10.08.2023

AU Engineering