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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Kass, M. A., Christiansen, A. V., Auken, E. & Larsen, J. J. (2021). Efficient reduction of powerline signals in magnetic data acquired from a moving platform. IEEE Transactions on Geoscience and Remote Sensing, 59(8), 7137-7146. Artikel 9246269. https://doi.org/10.1109/TGRS.2020.3029658

Larsen, J. J., Langhof, R. B., Kjær, M. W., Vang, M., Liu, L., Griffiths, M. & Grombacher, D. (2022). Efficient processing of surface NMR data with spectral analysis. Geophysical Journal International, 229(1), 286-298. https://doi.org/10.1093/gji/ggab472

Griffiths, M. P., Grombacher, D. J. & Larsen, J. J. (2021). Efficient numerical Bloch solutions for multipulse surface NMR. Geophysical Journal International, 227(3), 1905-1916. https://doi.org/10.1093/gji/ggab321

Pham, X. H. (2023). Efficient deep learning-based monocular 3D perception for agile robot navigation. Århus Universitet.

Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2020). Efficient Bloch-equation solvers for surface nuclear magnetic Resonance. Abstract fra AGU Fall Meeting 2020.

Jørgensen, R. N. (2010). Effects of the machine wheel load on grass yield. I P. Savoie, J. Villeneuve & R. Morisette (red.), XVIIth World Congress of the International Commission of Agricultural and Biosystems Engineering: Book of Abstracts (Bind XVII, s. 221). CIGR. https://www.researchgate.net/publication/280227190_Effects_of_the_machine_wheel_load_on_grass_yield

Green, O., Jørgensen, R. N., Kristensen, K., Bochtis, D. & Sørensen, C. A. G. (2010). Effect of machinery wheel load on grass yield. World Congress of the International Commission of Agricultural and Biosystems Engineering (CIGR), XVII. http://www.bioeng.ca/cigr2010/

Sridharan, K. S., Johnsen, E. L., Nielsen, A. H., Beniczky, S., Johansen, L. G., Sunde, N. & Østergaard, K. (2015). Effect of deep brain stimulation (DBS) and medication on somatosensory function in Parkinson’s disease (PD). Poster-session præsenteret på Nordic Congress of Clinical Neurophysiology, Helsingør, Danmark.

Asif, M. R., Bording, T. S., Barfod, A. S., Grombacher, D. J., Maurya, P. K., Christiansen, A. V., Auken, E. & Larsen, J. J. (2021). Effect of Data Pre-Processing on the Performance of Neural Networks for 1-D Transient Electromagnetic Forward Modeling. IEEE Access, 9, 34635-34646. https://doi.org/10.1109/ACCESS.2021.3061761

Asif, M. R., Bording, T. S., Barfod, A. S., Auken, E. & Larsen, J. J. (2020). Effect of Data Normalization on Neural Networks for the Forward Modelling of Transient Electromagnetic Data,. Abstract fra Near Surface Geoscience 2020.

Rehman, N., Ehsan, S., Naveed, K., McDonald-Maier, K. D. & Safdar, M. W. (2015). Dynamically sampled multivariate empirical mode decomposition. Electronics Letters, 51(24), 2049-2051. https://doi.org/10.1049/el.2015.1176

Rehman, N. U. & Mandic, D. P. (2014). Dynamically-Sampled Bivariate Empirical Mode Decomposition. IEEE Signal Processing Letters, 21(7), 857-861. https://doi.org/10.1109/lsp.2014.2317773

Naveed, K., Shaukat, B. & Rehman, N. U. (2018). Dual tree complex wavelet transform-based signal denoising method exploiting neighbourhood dependencies and goodness-of-fit test. Royal Society Open Science, 5(9), 180436. https://doi.org/10.1098/rsos.180436

Olesen, C. R., Nyholm Jørgensen, R., Laursen, M. S., Larsen, R. & Rosendahl Bjorholm, S. (2017, jun. 1). Droner og losurin. Danmarks Jægerforbund. http://www.jaegerforbundet.dk/om-dj/nyhedsarkiv/2017/droner-og-losurin/

Mortensen, A. K., Laursen, M. S., Nyholm Jørgensen, R. & Gislum, R. (2019). Drone dataflow - a MATLAB toolbox for extracting plots from images captured by a UAV. I J. V. Stafford (red.), Precision Agriculture '19 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019 (s. 959-965). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-888-9_118

Schultz, N. (red.), Tan, S. (red.), Sørensen, J. K. (red.), Karamolegkos, P., Larsen, J. E., Larsen, L. B., Nikolakopoulos, G., Olseni, C., Patriakis, C. Z., Pedersen, C. F., Pedersen, J. S., Proschowsky, M., Protonotarios, V., Roswall, R., Saugstrup, D., Sørensen, L., Bessler, S., Hammershøj, A., Heinze, E. ... Xu, C. (2006). Draft User Functionalities and Interfaces of PN Services (Low-Fi Prototyping). Information Society Technologies, IST-FP6-IP-027396, My Personal Adaptive Global NET (MAGNET) Beyond, EU.

Olsson, P.-I., Fiandaca, G., Larsen, J. J., Dahlin, T. & Auken, E. (2016). Doubling the spectrum of time-domain induced polarization: removal of non-linear self-potential drift, harmonic noise and spikes, tapered gating, and uncertainty estimation. Abstract fra IP2016 - 4th International Workshop on Induced Polarization, Aarhus , Danmark.

Fiandaca, G., Olsson, P.-I., Auken, E., Larsen, J. J., Maurya, P. K. & Dahlin, T. (2015). Doubling the Spectrum of Time-Domain Induced Polarization: Removal of Harmonic Noise and Self-Potential Drift. Abstract fra AGU Fall Meeting 2015, San Fransisco, USA. https://agu.confex.com/agu/fm15/meetingapp.cgi/Paper/75469

Fiandaca, G., Olsson, P. I., Larsen, J. J., Dahlin, T. & Auken, E. (2016). Doubling the spectrum of time-domain induced polarization by harmonic de-noising, drift/spike removal and tapered gating. I 22nd European Meeting of Environmental and Engineering Geophysics, Near Surface Geoscience 2016 European Association of Geoscientists and Engineers, EAGE. https://doi.org/10.3997/2214-4609.201602021

Olsson, P.-I., Fiandaca, G., Larsen, J. J., Dahlin, T. & Auken, E. (2016). Doubling the spectrum of time-domain induced polarization by harmonic de-noising, drift correction, spike removal, tapered gating and data uncertainty estimation. Geophysical Journal International, 207(2), 774-784. Artikel ggw260. https://doi.org/10.1093/gji/ggw260

Sarabakha, A., Fu, C. & Kayacan, E. (2017). Double-Input Interval Type-2 Fuzzy Logic Controllers: Analysis and Design. I 2017 IEEE International Conference on Fuzzy Systems, FUZZ 2017 (s. 1-6). Artikel 8015485 IEEE . https://doi.org/10.1109/FUZZ-IEEE.2017.8015485

Asif, M. R., Foged, N., Bording, T. S., Larsen, J. J. & Christiansen, A. V. (2023). DL-RMD: a geophysically constrained electromagnetic resistivity model database for deep learning applications. Earth System Science Data, 15(3), 1389-1401. https://doi.org/10.5194/essd-2022-345, https://doi.org/10.5194/essd-15-1389-2023

Kayacan, E., Kayacan, E., Ramon, H. & Saeys, W. (2014). Distributed nonlinear model predictive control of an autonomous tractor-trailer. Mechatronics, 24(8), 926-933. https://doi.org/10.1016/j.mechatronics.2014.03.007

Madsen, S. L., Mortensen, A. K., Nyholm Jørgensen, R. & Karstoft, H. (2019). Disentangling Information in Artificial Images of Plant Seedlings Using Semi-Supervised GAN. Remote Sensing, 11(22), Artikel 2671. https://doi.org/10.3390/rs11222671

So, P., Sarabakha, A., Wu, F., Culha, U., Abu-Dakka, F. & Haddadin, S. (2024). Digital Robot Judge: Building a Task-centric Performance Database of Real-World Manipulation With Electronic Task Boards. Robotics Automation Magazine, IEEE.

Sridharan, K. S., Højlund, A., Johnsen, E. L., Sunde, N., Johansen, L. G., Beniczky, S. & Østergaard, K. (2017). Differentiated effects of deep brain stimulation and medication on somatosensory processing in Parkinson's disease. Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology, 128(7), 1327-1336. https://doi.org/10.1016/j.clinph.2017.04.014

Laursen, M. S., Nyholm Jørgensen, R., Midtiby, H. S., Jensen, K., Christiansen, M. P., Giselsson, T. M., Mortensen, A. K. & Jensen, P. K. (2016). Dicotyledon Weed Quantification Algorithm for Selective Herbicide Application in Maize Crops. Sensors, 16(11), Artikel 1848. https://doi.org/10.3390/s16111848

Laursen, M. S., Nyholm Jørgensen, R., Skov Midtiby, H., Mortensen, A. K. & Santhome, S. (2017). Dicotyledon Weed Quantification Algorithm for Selective Herbicide Application in Maize Crops: Statistical Evaluation of the Potential Herbicide Savings. International Journal of Agricultural and Biosystems Engineering, 11(4), 1285. https://www.waset.org/abstracts/62424

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

Ahrendt, P., Gregersen, T. & Karstoft, H. (2011). Development of a real-time computer vision system for tracking loose-housed pigs. Computers and Electronics in Agriculture, 76(2), 169-174. https://doi.org/10.1016/j.compag.2011.01.011

Yan, R.-J., Leong Low, C., Duan, J., Liu, L., Kayacan, E., Chen, I.-M. & Tiong, R. (2017). Development of a Novel Post-Construction Quality Assessment Robot System. I 2016 14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016 (s. 1-6). Artikel 7838741 IEEE . https://doi.org/10.1109/ICARCV.2016.7838741

Jørgensen, R. (2006). Det lugter af rævekage. Horsens Folkeblad.

Dyrmann, M., Nyholm Jørgensen, R. & Midtiby, H. S. (2017). Detection of weed locations in leaf occluded cereal crops using a fully convolutional neural network. Advances in Animal Biosciences, 8(2), 842-847. https://doi.org/10.1017/S2040470017000206

Thanh Nguyen, T., Vandevoorde, K., Wouters, N., Kayacan, E., G. de Baerdemaeker, J. & Saeys, W. (2016). Detection of red and bicoloured apples on tree with an RGB-D camera. Biosystems Engineering, 146, 33-44. https://doi.org/10.1016/j.biosystemseng.2016.01.007

Steen, K. A., Therkildsen, O. R., Green , O. & Karstoft, H. (2015). Detection of Bird Nests during Mechanical Weeding by Incremental Background Modeling and Visual Saliency. Sensors, 15(3), 5096-5111. https://doi.org/10.3390/s150305096

Chen, Q., Lang, X., Lu, S., Rehman, N. U., Xie, L. & Su, H. (2021). Detection and root cause analysis of multiple plant-wide oscillations using multivariate nonlinear chirp mode decomposition and multivariate Granger causality. Computers and Chemical Engineering, 147, Artikel 107231. https://doi.org/10.1016/j.compchemeng.2021.107231

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

Skovsen, S. K., Kutugata, M., Jennewein, J., Reberg-Horton, C. S. & Mirsky, S. B. (2023). Detailed Species Competition Mapping of Mixed Cover Crop Species Using Tractor Mounted Color Camera and Computer Vision. Abstract fra 2023 ASA/CSSA/SSSA International Annual Meeting, St. Louis, Missouri, USA.

Larsen, J. J. (2016). Despiking of Surface-NMR Data Using a Model-based Approach. I Near Surface Geoscience 2016 : 22nd European Meeting of Environmental and Engineering Geophysics (Bind 2016). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.201602068

Larsen, J. J. & Auken, E. (2015). Despiking of magnetic resonance sounding signals. Afhandling præsenteret på The 6th International Workshop on Magnetic Resonance, Aarhus , Danmark. http://hgg.au.dk/fileadmin/www.dna18.au.dk/MRS2015_program.pdf

Kayacan, E., Kaynak, O., H. Abiyev, R., Tørresen, J., Høvin, M. & Glette, K. (2010). Design of an Adaptive Interval Type-2 Fuzzy Logic Controller for the Position Control of a Servo System with an Intelligent Sensor. I Fuzzy Systems (FUZZ), 2010 IEEE International Conference on (s. 1125-1132). IEEE . https://doi.org/10.1109/FUZZY.2010.5584629

Shahrak Nadimi, E., Andersson, K. J., Jørgensen, R. N., Maagaard, J., Mathiassen, S. K. & Christensen, S. (2009). Designing, modeling and controlling a novel autonomous laser weeding system. I Conference papers World Congress on Computers in Agriculture. https://elibrary.asabe.org/pdfviewer.asp?param1=s:/8y9u8/q8qu/tq9q/5tv/H/Cs43IGGP/KP_dqty2y.5tv&param2=HI/I/IGIK&param3=HJG.IIL.IH.IK&param4=29077

Christiansen, M. P., Laursen, M. S., Nyholm Jørgensen, R., Skovsen, S. & Gislum, R. (2017). Designing and Testing a UAV Mapping System for Agricultural Field Surveying. Sensors, 17(12), Artikel 2703. https://doi.org/10.3390/s17122703

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

Mehndiratta, M., Kayacan, E. & Kumbasar, T. (2016). Design and Experimental Validation of Single Input Type-2 Fuzzy PID Controllers as Applied to 3 DOF Helicopter Testbed. I 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016 (s. 1584-1591). Artikel 07737879 IEEE. https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7737879

Nyholm Jørgensen, R. & Christiansen, M. P. (2018). Demonstration of plant labs web explorer combined with data from Danish field boundaries. Billeder, Video- og Lydoptagelser (digital), YouTube. https://www.youtube.com/watch?v=ExlN0XrIx7E

Westh Nicolajsen, H., Ahola, T., Fleury, A. M., Milkova Ilieva, T., Eg Larsen, J., Larsen, L. B., G. Nikolakopoulos, I., Z. Patrikakis, C., Pedersen, C. F., Roswall, R., Schultz, N. & Tolstrup Sørensen, L. (2007). Defining Usability of PN Services. Information Society Technologies, IST-FP6-IP-027396, My Personal Adaptive Global NET (MAGNET) Beyond, EU.

Sørensen, R. A., Nielsen, M. & Karstoft, H. (2019). Deep Reinforcement Learning for Route Optimization in Baggage Handling Systems. I S. Y. Yurish (red.), Advances in Signal Processing and Artificial Intelligence: Proceedings of the 1st International Conference on Advances in Signal Processing and Artifical Intelligence (s. 29-33). Artikel 11 IFSA Publishing.

Camci, E., Campolo, D. & Kayacan, E. (2020). Deep Reinforcement Learning for Motion Planning of Quadrotors Using Raw Depth Images. I 2020 International Joint Conference on Neural Networks, IJCNN 2020 - Proceedings Artikel 9207490 IEEE. https://doi.org/10.1109/IJCNN48605.2020.9207490

Pham, H. X., Ugurlu, H. I., Fevre, J. L., Bardakci, D. & Kayacan, E. (2022). Deep learning for vision-based navigation in autonomous drone racing. I A. Iosifidis & A. Tefas (red.), Deep Learning for Robot Perception and Cognition (s. 371-406). Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00020-8

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Revideret 10.08.2023

AU Engineering