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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Naveed, K. & Rehman, N. U. (2020). Wavelet based multivariate signal denoising using Mahalanobis distance and EDF statistics. IEEE Transactions on Signal Processing, 68, 5997-6010. Artikel 9234624. https://doi.org/10.1109/TSP.2020.3029659

Bjerge, K., Frigaard, C. E., Mikkelsen, P. H., Nielsen, T. H., Misbih, M. & Kryger, P. (2019). A computer vision system to monitor the infestation level of Varroa destructor in a honeybee colony. Computers and Electronics in Agriculture, 164(September), Artikel 104898. https://doi.org/10.1016/j.compag.2019.104898

Mehndiratta, M. & Kayacan, E. (2019). A constrained instantaneous learning approach for aerial package delivery robots: onboard implementation and experimental results. Autonomous Robots, 43(8), 2209-2228. https://doi.org/10.1007/s10514-019-09875-y

Teimouri, N., Christiansen, M. P., Nyholm Jørgensen, R. & Grøn Sørensen, C. (2019). A deep learning-based approach for crop classification using dual-polarimetric C-band radar data.

Imanberdiyev, N. & Kayacan, E. (2019). A fast learning control strategy for unmanned aerial manipulators. Journal of Intelligent and Robotic Systems, 94(3-4), 805-824. https://doi.org/10.1007/s10846-018-0884-7

Naveed, K., Ehsan, S., McDonald-Maier, K. D. & Ur Rehman, N. (2019). A multiscale denoising framework using detection theory with application to images from CMOS/CCD sensors. Sensors (Switzerland), 19(1), Artikel 206. https://doi.org/10.3390/s19010206

Imanberdiyev, N., Monica, J. & Kayacan, E. (2019). A multi-task velocity-based redundancy resolution strategy for unmanned aerial manipulators. I 2019 18th European Control Conference, ECC 2019 (s. 1130-1135). Artikel 8796272 IEEE. https://doi.org/10.23919/ECC.2019.8796272

Khawaja, A., Khan, T. M., Naveed, K., Naqvi, S. S., Rehman, N. U. & Nawaz, S. J. (2019). An Improved Retinal Vessel Segmentation Framework Using Frangi Filter Coupled With the Probabilistic Patch Based Denoiser. IEEE Access, 7, 164344-164361. https://doi.org/10.1109/access.2019.2953259

Teimouri, N., Dyrmann, M. & Nyholm Jørgensen, R. (2019). A novel spatio-temporal FCN-LSTM Network for Recognizing Various Crop Types Using Multi-Temporal Radar Images. Remote Sensing, 11(8), Artikel 990. https://doi.org/10.3390/rs11080990

Liu, L., Grombacher, D., Auken, E. & Juul Larsen, J. (2019). Apsu: A wireless multichannel receiver system for surface nuclear magnetic resonance groundwater investigations. Geoscientific Instrumentation, Methods and Data Systems, 8(1), 1-11. https://doi.org/10.5194/gi-8-1-2019

Larsen, J. J., Liu, L., Grombacher, D., Osterman, G. & Auken, E. (2019). Apsu - A new surface nmr instrument for hydrogeophysics. Afhandling præsenteret på 25th European Meeting of Environmental and Engineering Geophysics, Held at Near Surface Geoscience Conference and Exhibition 2019, NSG 2019, The Hague, Holland.

Saleem, S., Naqvi, S. S., Manzoor, T., Saeed, A., Rehman, N. U. & Mirza, J. (2019). A Strategy for Classification of "Vaginal vs. Cesarean Section" Delivery: Bivariate Empirical Mode Decomposition of Cardiotocographic Recordings. Frontiers in Physiology, 10. https://doi.org/10.3389/fphys.2019.00246

Bjerge, K., Fynbo, H. O. U. & Johansen, J. G. (2019). A system on programmable chip design of a digitizer with improved trapezoidal filter validation. Microprocessors and Microsystems, 65, 7-13. https://doi.org/10.1016/j.micpro.2018.12.004

Kragh, M. F., Rimestad, J., Berntsen, J. & Karstoft, H. (2019). Automatic grading of human blastocysts from time-lapse imaging. Computers in Biology and Medicine, 115, Artikel 103494. https://doi.org/10.1016/j.compbiomed.2019.103494

Kragh, M. F., Rimestad, J., Berntsen, J. & Karstoft, H. (2019). Automatic morphological grading of human blastocysts with time-lapse imaging and artificial intelligence. Abstract fra ESHRE, Vienna, Østrig. https://www.eshre.eu/ESHRE2019/Programme/Searchable#!abstractdetails/0000573820

Gislum, R., Nyholm Jørgensen, R., Thomsen, I. K., Hansen, E. M. & Olesen, J. E., (2019). Beskrivelse af setup for vidensindsamling og måling af NDVI-værdi i pilotprojekt om biomasse, Nr. 2019-760-001283, 3 s., jul. 03, 2019.

Liu, L., Grombacher, D. J., Auken, E. & Larsen, J. J. (2019). Complex envelope retrieval for surface nuclear magnetic resonance data using spectral analysis. Geophysical Journal International, 217(2), 894-905. https://doi.org/10.1093/gji/ggz068

Rehman, N. U., Naveed, K. & Khan, B. (2019). Data-Driven Multivariate Signal Denoising Using Mahalanobis Distance. IEEE Signal Processing Letters, 26(9), 1408-1412. https://doi.org/10.1109/LSP.2019.2932715

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.

Frederiksen, T. & Larsen, J. J. (2019). Detection of Capacitive Couplings in Ground-Based TEM Data with a 1D Convolutional Neural Network. Afhandling præsenteret på 25th European Meeting of Environmental and Engineering Geophysics, Held at Near Surface Geoscience Conference and Exhibition 2019, NSG 2019, The Hague, Holland.

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

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

Malik, Q. W., Rehman, N. U., Gull, S., Ehsan, S. & McDonald-Maier, K. D. (2019). FPGA-Based Real-Time Implementation of Bivariate Empirical Mode Decomposition. Circuits, Systems, and Signal Processing, 38(1), 118-137. https://doi.org/10.1007/s00034-018-0844-2

Gul, S., Siddiqui, M. F. & Rehman, N. U. (2019). FPGA Based Real-Time Implementation of Online EMD With Fixed Point Architecture. IEEE Access, 7, 176565-176577. https://doi.org/10.1109/access.2019.2957819

Madsen, S. L., Dyrmann, M., Nyholm Jørgensen, R. & Karstoft, H. (2019). Generating artificial images of plant seedlings using generative adversarial networks. Biosystems Engineering, 187, 147-159. https://doi.org/10.1016/j.biosystemseng.2019.09.005

Sarabakha, A., Fu, C. & Kayacan, E. (2019). Intuit before tuning: Type-1 and type-2 fuzzy logic controllers. Applied Soft Computing Journal, 81, Artikel 105495. https://doi.org/10.1016/j.asoc.2019.105495

Zhou, S., Helwa, M. K., Schoellig, A. P., Sarabakha, A. & Kayacan, E. (2019). Knowledge transfer between robots with similar dynamics for high-accuracy impromptu trajectory tracking. I 2019 18th European Control Conference, ECC 2019 Artikel 8796140 IEEE. https://doi.org/10.23919/ECC.2019.8796140

Mehndiratta, M., Kayacan, E., Patel, S., Kayacan, E. & Chowdhary, G. (2019). Learning-based Fast Nonlinear Model Predictive Control for Custom-made 3D Printed Ground and Aerial Robots. I S. V. Rakovic & W. Levine (red.), Handbook of Model Predictive Control (1 udg., s. 581-605). Birkhäuser Verlag. https://doi.org/10.1007/978-3-319-77489-3_24

Govdeli, Y., Bin Muzaffar, S. M., Raj, R., Elhadidi, B. & Kayacan, E. (2019). Learning Control of Tandem-Wing Tilt-Rotor UAV with Unsteady Aerodynamic Model. I 2019 IEEE International Conference on Fuzzy Systems, FUZZ 2019 Artikel 8859023 IEEE. https://doi.org/10.1109/FUZZ-IEEE.2019.8859023

Camci, E. & Kayacan, E. (2019). Learning motion primitives for planning swift maneuvers of quadrotor. Autonomous Robots, 43(7), 1733-1745. https://doi.org/10.1007/s10514-019-09831-w

Asif, M. R., Qi, C., Wang, T., Fareed, M. S. & Khan, S. (2019). License plate detection for multi-national vehicles – a generalized approach. Multimedia Tools and Applications, 78(24), 35585-35606. https://doi.org/10.1007/s11042-019-08199-4

Asif, M. R., Qi, C., Wang, T., Sadiq Fareed, M. & Ali Reza, S. (2019). License Plate Detection for Multi-national Vehicles: An Illumination Invariant Approach in Multi-lane Environment. Computers & Electrical Engineering, 78, 132-147. https://doi.org/10.1016/j.compeleceng.2019.07.012

Klausen, K. C., Pagels, K. Ø., Bjerre, J. (red.) & Pedersen, C. F. (red.) (2019). LoRa and LoRaWAN Case Studies. European Regional Development Fund and Central Denmark Region.

Somerville, G. J., Nyholm Jørgensen, R., Bojer, O. M., Rydahl, P., Dyrmann, M., Andersen, P., Jensen, N.-P. & Green, O. (2019). Marrying futuristic weed mapping with current herbicide sprayer capacities. I J. V. Stafford (red.), Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019 (s. 231-237). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-888-9_28

Naveed, K., Shaukat, B., Ehsan, S., Mcdonald-Maier, K. D., Rehman, N. U. & Baghaie, A. (red.) (2019). Multiscale image denoising using goodness-of-fit test based on EDF statistics. P L o S One, 14(5), e0216197. https://doi.org/10.1371/journal.pone.0216197

Rehman, N. U. & Aftab, H. (2019). Multivariate Variational Mode Decomposition. IEEE Transactions on Signal Processing, 67(23), 6039. Artikel 8890883. https://doi.org/10.1109/TSP.2019.2951223

Eriksen, J., Frandsen, T. S., Knudsen, L., Skovsen, S., Nyholm Jørgensen, R., Steen, K. A., Green, O. & Rasmussen, J. (2019). Nitrogen fertilization of grass-clover leys. I O. Huguenin-Elie, B. Studer, R. Kölliker, D. Reheul, M. Probo, P. Barre, U. Feuerstein, I. Roldan-Ruiz, P. Mariotte & A. Hopkins (red.), Improving sown grasslands through breeding and management: Proceedings of the Joint 20th Symposium of the European Grassland Federation and the 33rd Meeting of the EUCARPIA Section "Fodder Crops and Amenity Grasses", Zürich, Switzerland, 24-27 June 2019 (s. 103-109). Wageningen Academic Publishers.

Ma, X., Hegarty, P. J., Jørgensen, K. F. & Larsen, J. J. (2019). Nonlinear distortion reduction in sound zones by constraining individual loudspeaker control effort. Journal of the Audio Engineering Society, 67(9), 641-654. https://doi.org/10.17743/jaes.2019.0015

Sarabakha, A. & Kayacan, E. (2019). Online deep learning for improved trajectory tracking of unmanned aerial vehicles using expert knowledge. I 2019 International Conference on Robotics and Automation, ICRA 2019 (s. 7727-7733). Artikel 8794314 IEEE. https://doi.org/10.1109/ICRA.2019.8794314

Camci, E. & Kayacan, E. (2019). Planning swift maneuvers of quadcopter using motion primitives explored by reinforcement learning. I Proceedings of the American Control Conference: 2019 American Control Conference, ACC 2019 (s. 279-285). Artikel 8815352 IEEE.

Christiansen, M. P., Teimouri, N., Laursen, M. S., Mikkelsen, B. F., Jorgensen, R. N. & Sorensen, C. A. G. (2019). Preprocessed sentinel-1 data via a web service focused on agricultural field monitoring. IEEE Access, 7(1), 65139-65149. Artikel 8715769. https://doi.org/10.1109/ACCESS.2019.2917063

Kremer, T., Juul Larsen, J. & Nguyen, F. (2019). Processing harmonic EM noise with multiple or unstable frequency content in surface NMR surveys. Geophysical Journal International, 219(2), 753-775. https://doi.org/10.1093/gji/ggz307

Yan, R. J., Kayacan, E., Chen, I. M., Tiong, L. K. & Wu, J. (2019). QuicaBot: Quality Inspection and Assessment Robot. IEEE Transactions on Automation Science and Engineering, 16(2), 506-517. https://doi.org/10.1109/TASE.2018.2829927

Nyholm Jørgensen, R., Laursen, M. S., Teimouri, N., Madsen, S. L., Dyrmann, M., Somerville, G. J. & Mathiassen, S. K. (2019). RoboWeedMaps - Automated weed detection and mapping - Invited talk at SSWM 2019, SDU, Odense Denmark. Billeder, Video- og Lydoptagelser (digital), YouTube.

Nyholm Jørgensen, R. (2019). RoboWeedMaps præsenterer pletsprøjtning på FutureCropping demodag den 9 oktober 2019. Billeder, Video- og Lydoptagelser (digital), YouTube. https://www.youtube.com/watch?v=YKCR-hARLS8&feature=youtu.be

Nyholm Jørgensen, R. (2019). RoboWeedMaps - Walking the weed maps with your mobile phone. Billeder, Video- og Lydoptagelser (digital), YouTube. https://www.youtube.com/watch?v=9rKahKe_a5c&t=108s

Farkhani, S., Kragh, M. F., Christiansen, P. H., Nyholm Jørgensen, R. & Karstoft, H. (2019). Sparse-to-Dense Depth Completion in Precision Farming. I Proceedings of the 3rd International Conference on Vision, Image and Signal Processing, ICVISP 2019: Proceedings of the 3rd International Conference on Vision, Image and Signal Processing Artikel 35 Association for Computing Machinery. https://doi.org/10.1145/3387168.3387230

Skovsen, S., Laursen, M. S., Gislum, R., Eriksen, J., Dyrmann, M., Mortensen, A. K., Farkhani, S., Karstoft, H., Jensen, N.-P. & Nyholm Jørgensen, R. (2019). Species distribution mapping of grass clover leys using images for targeted nitrogen fertilization. I J. V. Stafford (red.), Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019 (s. 639-645). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-888-9_79

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

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. Datasæt https://vision.eng.au.dk/grass-clover-dataset/

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Revideret 10.08.2023

AU Engineering