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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Gokhale, R., Wan, Y., Mehndiratta, M. & Kayacan, E. (2018). Fixed-wing Vertical-takeoff-and-landing UAV with Additive Manufacturing: A dual-rotor Version. I Proceedings of the 3rd International Conference on Progress in Additive Manufacturing (Pro-AM 2018) (Bind 2018-May, s. 250-255) https://doi.org/10.25341/D4Z30H

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

Laursen, M. S., Nyholm Jørgensen, R., Gislum, R. & Christiansen, M. P. (2017). First attempt at crop mapping with Velodyne VLP16 and Matrice 100. Billeder, Video- og Lydoptagelser (digital), YouTube. https://www.youtube.com/watch?v=rzTScFbkdG0

Bäckström, T., Pedersen, C. F., Fischer, J. & Pietrzyk, G. (2015). Finding Line Spectral Frequencies Using the Fast Fourier Transform. I Proceedings of the 2015 IEEE International Conference on Acoustics, Speech and Signal Processing: ICASSP (s. 5122-5126). IEEE. https://doi.org/10.1109/ICASSP.2015.7178947

Olesen, H., Jiang, B., Schultz, N., Sørensen, L., Saugstrup, D., Skouby, K. E., Pedersen, C. F., Larsen, L. B., Bjorksten, M., Kaldanis, V., Prasad, R., Olséni, C., Roswall, R. & Vila, J. (2005). Final user requirements for the PN service architecture. Information Society Technologies, My Personal Adaptive Global NET (MAGNET), IST 507102.

Rehman, N. U. & Mandic, D. P. (2011). Filter Bank Property of Multivariate Empirical Mode Decomposition. IEEE Transactions on Signal Processing, 59(5), 2421-2426. https://doi.org/10.1109/tsp.2011.2106779

Bjerge, K., Pinoy, N., Karstoft, H. & Høye, T. T. (2023). Field trials with automated moth monitoring in three different habitats of Denmark. Abstract fra 2023 Butterfly Conservation Symposium, Bedfordshire , Storbritannien.

Nyholm Jørgensen, R., Brandt , M. B., Schmidt, T., Laursen, M. S., Larsen, R., Nørremark, M., Midtiby, H. S. & Christiansen, P. (2015). Field trial design using semi-automated conventional machinery and aerial drone imaging for outlier identification. I J. V. Stafford (red.), Precision agriculture '15: Papers presented at the 10th European Conference on Precision Engineering (Bind 2015, s. 151-158). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-814-8_18

Giselsson , T. M. & Nyholm Jørgensen, R. (2013). Field Simulation Method for Testing Computer Vision Algorithms. Afhandling præsenteret på CIOSTA XXXV Conference, Billund, Danmark.

Jørgensen, B. J. & Jørgensen, R. (1997). Field scale and laboratory study of factors affecting N2O emission from a rye stubble field on sandy loam soil. Biology and Fertility of Soils, 25, 366-371.

Kragh, M. F., Christiansen, P., Laursen, M. S., Larsen, M., Steen, K. A., Green, O., Karstoft, H. & Jørgensen, R. N. (2017). FieldSAFE: Dataset for Obstacle Detection in Agriculture. Sensors, 17(11), Artikel 2579. https://doi.org/10.3390/s17112579

Bjerge, K., Bodesheim, P. & Karstoft, H. (2024). Few-Shot Learning with Novelty Detection. 340-363. Afhandling præsenteret på DeLTA 2024 - 5th International Conference on Deep Learning Theory and Applications. https://doi.org/10.1007/978-3-031-66694-0_21

Jørgensen, R., Sørensen, C. A. G., Jensen, H. F., Andersen, B. H., Jensen, K. & Maagaard, J. (2007). FeederAnt - An autonomous mobile unit feeding outdoor pigs: Paper No. 077022. I Ikke angivet ASABE - American Society of Agricultural and Biological Engineers. http://asae.frymulti.com/techpapers.asp?confid=min2007

Ahmadieh Khanesar, M., Kayacan, E., Reyhanoglu, M. & Kaynak, O. (2015). Feedback Error Learning Control of Magnetic Satellites Using Type-2 Fuzzy Neural Networks With Elliptic Membership Functions. IEEE Transactions on Cybernetics, 45(4), 858-868. https://doi.org/10.1109/TCYB.2015.2388758

Griffiths, M. P. & Hardenberg, M. (2024). Feasibility study of steady-state surface NMR with adiabatic pulses. Afhandling præsenteret på EAGE Near Surface Geoscience, Helsinki, Finland.

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

Sørensen, C. A. G., Green, O., Nørremark, M., Jørgensen, R., Jensen, K., Maagaard, J. & Jensen, L. A. (2007). Feasibility study of a plant nursing robot performing weeding operations. Abstract fra NJF seminar: Modellling in Agriculture, Jelgava, Letland.

Sørensen, C. A. G., Green, O., Nørremark, M., Jørgensen, R. N., Jensen, K., Maagaard, J. & Jensen, L. A. (2009). Feasibility study of a plant nursing robot performing weeding operations. I Proceedings of the NJF Seminar Nordic Association of Agricultural Scientists.

Ong, Z. Q. G., Govdeli, Y., Ravindrababu, S. & Kayacan, E. (2018). Feasibility Studies of Postprocessing Techniques to Strenghten 3D Printed UAV Wing Structures. I Proceedings of the 3rd International Conference on Progress in Additive Manufacturing (Pro-AM 2018) (Bind 2018-May, s. 244-249) https://doi.org/10.25341/D4WW2K

Kusk, K., Nielsen, D. B., Thylstrup, T., Rasmussen, N. H., Jørvang , J., Pedersen, C. F. & Wagner, S. R. (2013). Feasibility of using a lightweight context-aware system for facilitating reliable home blood pressure self-measurements. I Proceedings of the 2013 7th International Conference on Pervasive Computing Technologies for Healthcare and Workshops: PervasiveHealth 2013 (s. 236-239) https://doi.org/10.4108/icst.pervasivehealth.2013.252107

Larsen, J. J., Kass, M. A., Grombacher, D. & Griffiths, M. P. (2024). Feasibility of Surface Nuclear Magnetic Resonance With Absurdly Long Excitation Pulses. Geophysical Research Letters, 51(20), Artikel e2024GL110826. https://doi.org/10.1029/2024GL110826

Kjaer-Rasmussen, A., Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2022). Fast removal of powerline harmonic noise from surface NMR datasets using a projection-based approach on graphical processing units. IEEE Geoscience and Remote Sensing Letters, 19, Artikel 8024005. https://doi.org/10.1109/LGRS.2021.3118064

Larsen, J. J., Dalgaard, E., Christiansen, P. & Auken, E. (2014). Fast mapping and analysis of anthropogenic noise sources affecting MRS experiments. I Near Surface Geoscience 2014 - 20th European Meeting of Environmental and Engineering Geophysics European Association of Geoscientists and Engineers. http://www.scopus.com/inward/record.url?scp=84908375168&partnerID=8YFLogxK

Dong, Y., Camci, E. & Kayacan, E. (2018). Faster RRT-based Nonholonomic Path Planning in 2D Building Environments Using Skeleton-constrained Path Biasing. Journal of Intelligent and Robotic Systems, 89(3-4), 387-401. https://doi.org/10.1007/s10846-017-0567-9

Miranda, J., Memon, M., Cabral, J., Ravelo, B., Wagner, S. R., Pedersen, C. F., Mathiesen, M. & Nielsen, C. (2017). Eye on Patient Care: Continuous Health Monitoring: Design and Implementation of a Wireless Platform for Healthcare Applications. IEEE Microwave Magazine, 18(2), 83-94. Artikel 7843732. https://doi.org/10.1109/MMM.2016.2635898

Vang, M. Ø., Grombacher, D., Larsen, J. J. & Christiansen, A. V. (2024). Extrapolating sparse SNMR data sets onto dense TEM coverage using spatially variable correlations. Abstract fra AGU Fall meeting 2024, Washington DC, USA.

Rasmussen, S., Skovgaard Nyboe, N., Mai, S. & Larsen, J. J. (2018). Extraction and use of noise models from transient electromagnetic data. Geophysics, 83(1), E37-E46. https://doi.org/10.1190/geo2017-0299.1

Rasmussen, S., Skovgaard Nyboe, N. & Larsen, J. J. (2016). Extraction and Use of Noise Models from Production-Mode Transient Electromagnetic Data. Abstract fra AGU Fall Meeting 2016, San Francisco, California, USA. https://agu.confex.com/agu/fm16/meetingapp.cgi/Paper/168217

Ahmadieh Khanesar, M., Kayacan, E., Teshnelab, M. & Kaynak, O. (2011). Extended Kalman Filter Based Learning Algorithm for Type-2 Fuzzy Logic Systems and its Experimental Evaluation. IEEE Transactions on Industrial Electronics, 59(11), 4443-4455. https://doi.org/10.1109/TIE.2011.2151822

Jørgensen, R., Hansen, P. M. & Bro, R. (2006). Exploratory study of winter wheat reflectance during vegetative growth using three-mode component analysis. International Journal of Remote Sensing, 27(5), 919-937.

Cigdem, O., Kayacan, E. & Kaynak, O. (2011). Experimental Study of an Interval Type-2 Fuzzy Neural Network Using Sliding-Mode Online Learning Algorithm. I Control Conference (ASCC), 2011 8th Asian (s. 1181-1186). IEEE. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5899240

Andersen, K. F., Pham, H. X., Ugurlu, H. I. & Kayacan, E. (2022). Event-based Navigation for Autonomous Drone Racing with Sparse Gated Recurrent Network. I 2022 European Control Conference (ECC) (s. 1342-1348). IEEE. https://doi.org/10.23919/ECC55457.2022.9838538

Ravindrababu, S., Govdeli, Y., Wei Wong, Z. & Kayacan, E. (2018). Evaluation of the Influence of Build and Print Orientations of Unmanned Aerial Vehicle Parts Fabricated Using Fused Deposition Modeling Process. Journal of Manufacturing Processes, 34(Part A), 659-666. https://doi.org/10.1016/j.jmapro.2018.07.007

Dyrmann, M., Midtiby, H. S. & Nyholm Jørgensen, R. (2016). Evaluation of intra variability between annotators of weed species in color images. Afhandling præsenteret på International Conference on Agricultural Engineering 2016, Aarhus, Danmark. http://conferences.au.dk/uploads/tx_powermail/cigr2016paper_annotation.pdf

Wagner, S. R., Beevi, F. H. A., Pedersen, C. F., Miranda, J., Cabral, J. & Ravelo, B. (2016). Evaluation of Caregivers' First Time Use of a Seamless Deployment Platform. I Proceedings of the International Conference on E-Health, EH 2016 - Part of the Multi Conference on Computer Science and Information Systems 2016 (s. 59-66). IADIS.

Grombacher, D., Griffiths, M. P. & Maurya, P. K. (2024). Estimation of transmitter-receiver separation for mobile ground-based transient electromagnetic systems using on-time gates. Abstract fra AGU Fall meeting 2024, Washington DC, USA.

Skovsen, S., Dyrmann, M., Mortensen, A. K., Steen, K. A., Green, O., Eriksen, J., Gislum, R., Nyholm Jørgensen, R. & Karstoft, H. (2017). Estimation of the Botanical Composition of Clover-Grass Leys from RGB Images Using Data Simulation and Fully Convolutional Neural Networks. Sensors, 17(12), Artikel 2930. https://doi.org/10.3390/s17122930

Nielsen, K. K., Andersen, H. J., Thomsen, A., Jørgensen, J. R. & Jørgensen, R. N. (2009). Estimation of leaf area index in cereal crops using red–green images. Biosystems Engineering, 104(3), 308-317. https://doi.org/10.1016/j.physletb.2003.10.071

Mashhadi, S. R., Grombacher, D., Pedersen, J. B., Jørgensen, F., Andersen, T. R. & Griffiths, M. P. (2024). Estimation of hydraulic conductivity variations within glacial sediments at Endelave island by borehole NMR data. I 30th European Meeting of Environmental and Engineering Geophysics, Held at the Near Surface Geoscience Conference and Exhibition 2024, NSG 2024 European Association of Geoscientists and Engineers, EAGE. https://doi.org/10.3997/2214-4609.202420047

Lakshminarayanan, S., Duecker, D., Sarabakha, A., Ganguly, A., Takayama, L. & Haddadin, S. (2024). Estimation of External Force acting on Underwater Robots. I 2024 IEEE 20th International Conference on Automation Science and Engineering, CASE 2024 (s. 3125-3131). IEEE. https://doi.org/10.1109/CASE59546.2024.10711608

Mortensen, A. K., Gislum, R., Larsen, R. & Nyholm Jørgensen, R. (2015). Estimation of above-ground dry matter and nitrogen uptake in catch crops using images acquired from an octocopter. I J. V. Stafford (red.), Precision agriculture '15: Papers presented at the 10th European Conference on Precision Agriculture (Bind 2015, s. 127-134). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-814-8_15

Mortensen, A. K., Laursen, M. S. & Nyholm Jørgensen, R. (2018). Estimation of Above-Ground Biomass and Nitrogen-Content of Agricultural Field Crops using Computer Vision. Billeder, Video- og Lydoptagelser (digital)

Mortensen, A. K., Karstoft, H., Søegaard, K. & Nyholm Jørgensen, R. (2014). Estimating the content of clover and grass in the sward using a consumer camera and image processing. Abstract fra Agromek and NJF joint seminar, Herning, Danmark. http://www.njf.nu/477.htm

Midtiby, H., Mosgaard Giselsson, T. & Jørgensen, R. N. (2012). Estimating plant stem emerging points (PSEPs) of sugar of beets in early growth stages. Biosystems Engineering, 111(1), 83-90. https://doi.org/10.1016/j.biosystemseng.2011.10.011

Jørgensen, R. N., Sørensen, C. G., Green, O. & Kristensen, K. (2009). Estimating impact on clover-grass yield caused by traffic intensities. I C. Lokhorst & P. W. G. Groot Koerkamp (red.), Precision livestock farming '09 (Bind 2009, s. 143-147). Wageningen Academic Publishers.

Jørgensen, R. N., Sørensen, C. A. G., Green, O. & Kristensen, K. (2010). Estimating impact on clover-grass yield caused by traffic intensities.

Larsen, P. G., Kristiansen, E. L., Bennedsen, J. & Bjerge, K. (2017). Enhancing non-technical skills by a multidisciplinary engineering summer school. European Journal of Engineering Education, 42(6), 1076-1096. https://doi.org/10.1080/03043797.2016.1261278

Banaei, M., Ghanami, F., Rafiei Foroushani, M., Boudjadar, J. & Khooban, M. H. (2020). Energy Management of Hybrid Diesel/Battery Ships in Multidisciplinary Emission Policy Areas. Energies, 13(16), Artikel 4179. https://doi.org/10.3390/en13164179

Rafiei Foroushani, M., Boudjadar, J. & Khooban, M. H. (2021). Energy Management of a Zero-Emission Ferry Boat with a Fuel Cell-Based Hybrid Energy System: Feasibility Assessment. IEEE Transactions on Industrial Electronics, 68(2), 1739-1748. https://doi.org/10.1109/TIE.2020.2992005

S. Nadimi, E., Blanes-Vidal, V. & Jørgensen, R. N. (2009). ENERGY GENERATION FOR WIRELESS SENSOR NETWORK BASED animal behavior monitoring system.

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Revideret 10.08.2023

AU Engineering