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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Jeppesen, J. H., Jacobsen, R. H., Nyholm Jørgensen, R. & Toftegaard, T. S. (2016). Towards Data-Driven Precision Agriculture using Open Data and Open Source Software. Afhandling præsenteret på International Conference on Agricultural Engineering 2016, Aarhus, Danmark.

Jeppesen, J. H., Jacobsen, R. H., Nyholm Jørgensen, R., Halberg, A. & Toftegaard, T. S. (2017). Identification of High-Variation Fields based on Open Satellite Imagery. Advances in Animal Biosciences, 8(2), 388-393. https://doi.org/10.1017/S2040470017000693

Jeppesen, J. H., Jacobsen, R. H. & Jorgensen, R. N. (2020). Crop Type Classification based on Machine Learning with Multitemporal Sentinel-1 Data. I A. Trost, A. Zemva & A. Skavhaug (red.), 2020 23rd Euromicro Conference on Digital System Design (DSD) (s. 557-564). IEEE. https://doi.org/10.1109/DSD51259.2020.00092

Jensen, B.-E., Andersen, H. J. & Jørgensen, R. (2004). Markrobotten arbejder. Agrologisk, 10, 12-13.

Jensen, L. A., Sørensen, C. A. G. & Jørgensen, R. (2008). Real-time internet-based traceability unit for mobile payload vehicles. I Proceedings of the XXXII CIOSTA-CIGR Section V Conference "Advances in Labour and Machinery Management for a Profitable Agriculture and Forestry" (s. 368-374). <Forlag uden navn>.

Jensen, L. A., Sørensen, C. G. & Jørgensen, R. N. (2008). Real-time Internet-Based Traceability Unit for Mobile Payload Vehicles. Agricultural Engineering International: CIGR Journal, 9. http://cigr-ejournal.tamu.edu/submissions/volume9/CIOSTA%2007%20003%20Jensen%204Jan2008.pdf

Jensen, K. L., Pedersen, C. F. & Larsen, L. B. (2007). Diasnet Mobile - A Personalized Mobile Diabetes Management and Advisory Service. Afhandling præsenteret på Conference on User Modelling, Corfu, Grækenland. http://www.iit.demokritos.gr/um2007/UM2007_WS7_PEL.pdf

Jensen, K. L., Pedersen, C. F. & Larsen, L. B. (2006). Towards useful and usable services in personal networks. I IEEE, 3rd Annual International Conference on Mobile and Ubiquitous System - Networking and Services (s. 1-8). https://doi.org/10.1109/MOBIQ.2006.340415

Jensen, K., Larsen, L. B., Olsen, K. S., Hansen, J. & Jørgensen, R. N. (2012). First results: Robot mapping of areas contaminated by landmines and unexploded ordnance. https://www.researchgate.net/publication/348751530_First_results_Robot_mapping_of_areas_contaminated_by_landmines_and_unexploded_ordnance

Jensen, K., Bøgild, A., Nielsen, S. H., Christiansen, M. P. & Jørgensen, R. N. (2011). FroboMind, proposing a conceptual architecture for agricultural field robot navigation. http://www.njf.nu/site/seminarRedirect.asp?intSeminarID=441&p=1004

Jensen, K., Jørgensen, R. N., Bøgild, A., Jørgensen, O. J., Nielsen, S. H. & Persson, R. B. (2011). Work in progress: Robotics mapping of landmine and UXO contaminated areas.

Jensen, T., Munkholm, L. J., Green, O. & Karstoft, H. (2014). A mobile surface scanner for soil studies. I Proceedings of the Second International Conference on Robotics, Associated High-Technologies and Equipment for Agriculture and Forestry - RHEA 2014: New trends in mobile robotics, perception and actuation for agriculture and forestry (s. 187-194)

Jensen, K., Larsen, M., Nielsen, S. H., Larsen, L. B., Olsen, K. S. & Nyholm Jørgensen, R. (2014). Towards an Open Software Platform for Field Robots in Precision Agriculture. Robotics, 3(2). https://doi.org/10.3390/robotics3020207

Jensen, K., Laursen, M. S., Midtiby, H. & Nyholm Jørgensen, R. (2013). Autonomous Precision Spraying Trials Using a Novel Cell Spray Implement Mounted on an Armadillo Tool Carrier. Afhandling præsenteret på CIOSTA XXXV Conference, Billund, Danmark. https://www.researchgate.net/publication/348751428_Autonomous_Precision_Spraying_Trials_Using_a_Novel_Cell_Spray_Implement_Mounted_on_an_Armadillo_Tool_Carrier

Jensen, T., Munkholm, L. J., Green , O. & Karstoft, H. (2015). Soil Surface Roughness Using Cumulated Gaussian Curvature. I L. Nalpantidis, V. Krüger, J.-O. Eklundh & A. Gasteratos (red.), Computer Vision Systems : 10th International Conference, ICVS 2015, Proceedings (s. 533-541). Springer. https://doi.org/10.1007/978-3-319-20904-3_48

Jensen, T. & Karstoft, H. (2014). Intelligent Soil Tillage. Abstract fra AGROMEK and NJF Joint Seminar on Future Arable Farming and Agricultural Engineering, Herning, Danmark.

Jensen, T., Green, O., Munkholm, L. J. & Karstoft, H. (2016). Fourier and granulometry methods on 3D images of soil surfaces for evaluating soil aggregate size distribution. American Society of Agricultural and Biological Engineers. Transactions, 32(5), 609-615. https://doi.org/10.13031/aea.32.10938

Jensen, K., Laursen, M. S., M. Neerup, M., Skriver, M., Larsen, R. & Nyholm Jørgensen, R. (2016). Towards UAV contour flight over agricultural fields using RTK-GNSS and a Digital Elevation Model. Afhandling præsenteret på International Conference on Agricultural Engineering 2016, Aarhus, Danmark. http://conferences.au.dk/uploads/tx_powermail/2016_cigr_towards_uav_contour_flight_over_agricultural_fields.pdf

Jensen, T., Karstoft, H., Green, O. & Munkholm, L. J. (2017). Assessing the effect of the seedbed cultivator leveling tines on soil surface properties using laser range scanners. Soil & Tillage Research, 167(April), 54-60. https://doi.org/10.1016/j.still.2016.11.006

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. https://doi.org/10.1101/2023.07.07.23292372

Jensen, M. H., Rasmussen, M., Mohamad, N., Dyrskog, S. E., Thorup, L., Mikic, N., Wismann, J., Grønhøj, M. H., Rom Poulsen, F., Nazari, M., Rehman, N. U., Simonsen, C. Z. & Korshoej, A. R. (2023). Safety, harm, and efficacy of IRRAflow® versus external ventricular drainage for intraventricular hemorrhage: A randomized clinical trial. medRxiv. https://doi.org/10.1101/2023.07.08.23292286

Jaume, G., Bozorgtabar, B., Ekenel, H. K., Thiran, J.-P. & Gabrani, M. (2018). Image-Level Attentional Context Modeling Using Nested-Graph Neural Networks.

Jaume, G., Pati, P., Bozorgtabar, B., Foncubierta-Rodríguez, A., Feroce, F., Anniciello, A. M., Rau, T., Thiran, J.-P., Gabrani, M. & Goksel, O. (2020). Quantifying Explainers of Graph Neural Networks in Computational Pathology.

Jakobsen, M. O., Herskind, E. S., Bjerge, K., Ahrendt, P., Pedersen, C. F. & Knudsen, M. B. (2021). Vibration signatures in ball bearings as a function of lubricant viscosity ratio κ, under alternating lubrication conditions. Tribology International, 156, Artikel 106840. https://doi.org/10.1016/j.triboint.2020.106840

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

Jain, A., Cunha, F., Bunsen, M. J., Cañas, J. S., Pasi, L., Pinoy, N., Helsing, F., Russo, J., Botham, M., Sabourin, M., Fréchette, J., Anctil, A., Lopez, Y., Navarro, E., Perez Pimentel, F., Zamora, A. C., Silva, J. A. R., Gagnon, J., August, T. ... Rolnick, D. (2025). Insect Identification in the Wild: The AMI Dataset. I A. Leonardis , E. Ricci , S. Roth , O. Russakovsky , T. Sattler & G. Varol (red.), Computer Vision – ECCV 2024 - 18th European Conference, Proceedings (s. 55-73). Springer. https://doi.org/10.1007/978-3-031-72913-3_4

Jain, S., Naveed, K., Oleksiienko, I., Iosifidis, A. & Pauwels, R. (2025). InJecteD: Analyzing Trajectories and Drift Dynamics in Denoising Diffusion Probabilistic Models for 2D Point Cloud Generation. CEUR Workshop Proceedings, 4072, 91-99.

Jacobsen, R. H., Hansen, F. O., Madsen, J. K., Karstoft, H., Mikkelsen, P. H., Skogberg, T. A., Rasmussen, E. S., Andersen, C., Alrøe, M. & Toftegaard, T. S. (2011). A Modular Platform for Wireless Body Area Network Research and Real-life Experiments: The ASE-BAN Testbed. International Journal on Advances in Networks and Services, 4(3-4), 257-277. http://www.iariajournals.org/networks_and_services/netser_v4_n34_2011_paged.pdf

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

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

Hussain, S., Qi, C., Asif, M. R. & Sohrab Khan, M. (2016). Active Contours for image segmentation using complex domain-based approach. IET Image Processing, 10(2), 121-129. https://doi.org/10.1049/iet-ipr.2014.0730

Høye, T. T., Mann, H. M. R. & Bjerge, K. (2020). Kamerabaseret overvågning af Insekter på grønne bytage. Aarhus University, DCE - Danish Centre for Environment and Energy. Videnskabelig rapport fra DCE - Nationalt Center for Miljø og Energi Nr. 371 https://dce2.au.dk/pub/SR371.pdf

Høye, T. T., Ärje, J., Bjerge, K., Hansen, O. L. P., Iosifidis, A., Leese, F., Mann, H. M. R., Meissner, K., Melvad, C. & Raitoharju, J. (2021). Deep learning and computer vision will transform entomology. Proceedings of the National Academy of Sciences (PNAS), 118(2), Artikel e2002545117. https://doi.org/10.1073/pnas.2002545117

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

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

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

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

Hein, A., Larsen, J. J. & D. Parsekian, A. (2017). Removal of Harmonic Noise from Surface Nuclear Magnetic Resonance Measurements in the Frequency Domain. Poster-session præsenteret på SAGEEP 2017, Denver, USA.

He, S., Cai, H., Christiansen, A. V. & Asif, M. R. (2023). A Novel Normalization Method of Transient Electromagnetic Data for Efficient Neural Network Training. Afhandling præsenteret på NSG2023 29th European Meeting of Environmental and Engineering Geophysics, Edinburgh , Storbritannien. https://doi.org/10.3997/2214-4609.202320125

Hasanvand , S., Rafiei Foroushani, M., Gheisarnejad, M. & Khooban, M. H. (2020). Reliable Power Scheduling of an Emission-Free Ship: Multi-Objective Deep Reinforcement Learning. IEEE Transactions on Transportation Electrification, 6(2), 832-843. Artikel 9046850. https://doi.org/10.1109/TTE.2020.2983247

Hardenberg, M., Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2024). Feasibility study of steady-state surface NMR with adiabatic pulses. I NSG2024, 30th European Meeting of Environmental and Engineering Geophysics (s. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420051

HAO, H., WANG, H., REHMAN, N. UR. & TIAN, H. (2016). A Study of the Characteristics of MEMD for Fractional Gaussian Noise. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, E99.A(6), 1228-1232. https://doi.org/10.1587/transfun.e99.a.1228

Hao, H., Wang, H. L. & Rehman, N. U. (2017). A joint framework for multivariate signal denoising using multivariate empirical mode decomposition. Signal Processing, 135, 263-273. https://doi.org/10.1016/j.sigpro.2017.01.022

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)

Hansen, P. M., Skjødt, P. & Jørgensen, R. (2003). Algorithm for variable nitrogen rate - application in winter wheat. I Proc. NJF Seminar 336 on Implementation of Precision Farming in Practical Agriculture. Skara, Sweden, June 2002. DIAS report - Plant Production 100 (s. 56-64)

Hansen, K. V., Brix, L. C., Pedersen, C. F., Haase, J. & Larsen, O. V. (2004). Modelling of interaction between a spatula and a human brain. Medical Image Analysis, 8(1), 23-33. https://doi.org/10.1016/j.media.2003.07.001

Hansen, M. K., Nyholm Jørgensen, R. & Pedersen, H. (2015). Object Detection and Terrain Classification in Agricultural Fields using 3D Lidar Data. I Computer Vision Systems: 10th International Conference, ICVS 2015, Proceedings (Bind 9163, s. 188-197). Springer. https://doi.org/10.1007/978-3-319-20904-3_18

Hansen, M. K., Underwood, J. & Karstoft, H. (2016). Self-supervised Traversability Assessment in Field Environments with Lidar and Camera. Poster-session præsenteret på International Conference on Agricultural Engineering 2016, Aarhus, Danmark.

Hansen, M. K., Christiansen, P., Korthals, T., Jungeblut, T., Karstoft, H. & Nyholm Jørgensen, R. (2016). Multi-modal Obstacle Detection and Evaluation of Occupancy Grid Mapping in Agriculture. Afhandling præsenteret på International Conference on Agricultural Engineering 2016, Aarhus, Danmark. http://conferences.au.dk/uploads/tx_powermail/2016cigr_-_multi-modal_obstacle_detection_and_evaluation_of_evidence_grid_mapping_in_agriculture.pdf

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