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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V. Topalev, A., Oniz, Y., Kayacan, E. & Kaynak, O. (2011). Neuro-Fuzzy Control of Antilock Braking System Using Sliding Mode Incremental Learning Algorithm. Neurocomputing, 74(11), 1883-1893. https://doi.org/10.1016/j.neucom.2010.07.035

V. Topalev, A., G. Shakev, N., Kaynak, O. & Kayacan, E. (2010). Neuro-adaptive Approach for Controlling a Quad-rotor Helicopter Using Sliding Mode Learning Algorithm. In IFAC Proceedings Volumes (10 ed., Vol. 43, pp. 94-99). Elsevier. https://doi.org/10.3182/20100826-3-TR-4015.00020

Iosifidis, A., Tefas, A. & Pitas, I. (2012). Neural representation and learning for multi-view human action recognition. In Neural Networks (IJCNN), The 2012 International Joint Conference on IEEE. https://doi.org/10.1109/IJCNN.2012.6252675

Tefas, A., Iosifidis, A. & Pitas, I. (2013). Neural Networks for Digital Media Analysis and Description. In L. Iliadis, H. Papadopoulos & C. Jayne (Eds.), Engineering Applications of Neural Networks: 14th International Conference, EANN 2013, Halkidiki, Greece, September 13-16, 2013 Proceedings, Part I (pp. 1-11). Springer. https://doi.org/10.1007/978-3-642-41013-0_1

Cao, G., Iosifidis, A. & Gabbouj, M. (2018). Neural class-specific regression for face verification. IET Biometrics, 7(1), 63-70. https://doi.org/10.1049/iet-bmt.2017.0081

Iosifidis, A., Tefas, A. & Pitas, I. (2015). Nearest Class Vector Classification for Large-Scale Learning Problems. In 2015 IEEE Trustcom/BigDataSE/ISPA (pp. 11-16). IEEE. https://doi.org/10.1109/Trustcom-BigDataSe-

Jørgensen, R., Jørgensen, B. J. & Nielsen, N. E. (1998). N2O emission immediately after rainfall in a rye stubble field. Soil Biology & Biochemistry, 30(4), 545-546.

Jørgensen, R. & Jørgensen, B. J. (1998). N2O emission from Miscanthus, rye and oilseed rape in relation to the net CO2-displacement. In Wörgetter, M. & Jørgensen, U. (eds.), Environmental aspects of energy crop production. Proc. IEA workshop, Brassimone, Italy, 1997. Report from BLT.

Jørgensen, R., Jørgensen, B. J., Nielsen, N. E., Maag, M. & Lind, A-M. (1997). N2O emission from energy crop fields with Miscanthus Giganteus and winter rye. Atmospheric Environment, 31, 2899-2904.

Jørgensen, R. N., Jørgensen, B. J., Nielsen, N. E., Maag, M. M. & Lind, A-M. (1997). N2O emission from energy crop fields of Miscanthus " giganteus" and winter rye. Atm. Environ, 31, 2899-2904.

Jørgensen, B. J. & Jørgensen, R. (1996). N2O emission from energy crop fields.

Iosifidis, A., Tefas, A. & Pitas, I. (2014). Multi-view Regularized Extreme Learning Machine for Human Action Recognition. In A. Likas, K. Blekas & D. Kalles (Eds.), Artificial Intelligence: Methods and Applications: 8th Hellenic Conference on AI, SETN 2014 (pp. 84-94). Springer. https://doi.org/10.1007/978-3-319-07064-3_7

Cao, G., Iosifidis, A. & Gabbouj, M. (2017). Multi-view Nonparametric Discriminant Analysis for Image Retrieval and Recognition. IEEE Signal Processing Letters, 24(10), 1537-1541. Article 8023967. https://doi.org/10.1109/LSP.2017.2748392

Iosifidis, A., Tefas, A., Nikolaidis, N. & Pitas, I. (2011). Multi-view Human Movement Recognition based on Fuzzy Distances and Linear Discriminant Analysis. Computer Vision and Image Understanding, 116(3), 347-360. https://doi.org/10.1016/j.cviu.2011.08.008

Iosifidis, A., Tefas, A. & Pitas, I. (2012). Multi-view Human Action Recognition under occlusion based on Fuzzy Distances and Neural Networks. In Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European (pp. 1129-1133). IEEE. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6334098

Iosifidis, A., Tefas, A. & Pitas, I. (2013). Multi-view human action recognition: a review. In Ninth International Conference on Intelligent Information Hiding and Multimedia Signal Processing IEEE. http://ikee.lib.auth.gr/record/263305/files/Iosifidis.pdf

Iosifidis, A., Tefas, A. & Pitas, I. (2012). Multi-view Action Recognition Based on Action Volumes, Fuzzy Distances and Cluster Discriminant Analysis. Signal Processing, 93(6), 1445-1457. https://doi.org/10.1016/j.sigpro.2012.08.015

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

Naveed, K., Mukhtar, S. & Ur Rehman, N. (2021). Multivariate Signal Denoising Based on Generic Multivariate Detrended Fluctuation Analysis. In 2021 IEEE Statistical Signal Processing Workshop, SSP 2021 (pp. 441-445). IEEE. https://doi.org/10.1109/SSP49050.2021.9513823

Ahmed, M. U., Rehman, N., Looney, D., Rutkowski, T. M., Kidmose, P. & Mandic, D. P. (2012). Multivariate entropy analysis with data-driven scales. In 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 3901-3904). IEEE. https://doi.org/10.1109/icassp.2012.6288770, https://doi.org/10.1109/ICASSP.2012.6288770

Asif, M. R., Qi, C., Hussain, S. & Sadiq Fareed, M. (2016). Multiple License Plate Detection for Chinese Vehicles in Dense Traffic Scenarios. IET Intelligent Transport Systems, 10(8). https://doi.org/10.1049/iet-its

Asif, M. R., Qi, C., Hussain, S., Sadiq Fareed, M. & Khan, S. (2017). Multinational vehicle license plate detection in complex backgrounds. Journal of Visual Communication and Image Representation, 46, 176-186. https://doi.org/10.1016/j.jvcir.2017.03.020

Sohrab, F., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2021). Multimodal Subspace Support Vector Data Description. Pattern Recognition, 110, Article 107648. https://doi.org/10.1016/j.patcog.2020.107648

Cao, G., Waris, M. A., Iosifidis, A. & Gabbouj, M. (2016). Multi-modal Subspace Learning with Dropout regularization for Cross-modal Recognition and Retrieval. In 2016 6th International Conference on Image Processing Theory, Tools and Applications, IPTA 2016 Article 7821032 IEEE. https://doi.org/10.1109/IPTA.2016.7821032

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. Paper presented at International Conference on Agricultural Engineering 2016, Aarhus, Denmark. http://conferences.au.dk/uploads/tx_powermail/2016cigr_-_multi-modal_obstacle_detection_and_evaluation_of_evidence_grid_mapping_in_agriculture.pdf

Korthals, T., Kragh, M. F., Christiansen, P., Karstoft, H., Nyholm Jørgensen, R. & Rückert, U. (2018). Multi-Modal Detection and Mapping of Static and Dynamic Obstacles in Agriculture for Process Evaluation. Frontiers in Robotics and AI, 5(MAR), Article 28. https://doi.org/10.3389/frobt.2018.00028

Tran, D. T., Yamac, M., Degerli, A., Gabbouj, M. & Iosifidis, A. (2021). Multilinear compressive learning. IEEE Transactions on Neural Networks and Learning Systems, 32(4), 1512-1524. Article 9070152. https://doi.org/10.1109/TNNLS.2020.2984831

Thanh Tran, D., Gabbouj, M. & Iosifidis, A. (2017). Multilinear Class-Specific Discriminant Analysis. Pattern Recognition Letters, 100, 131-136. https://doi.org/10.1016/j.patrec.2017.10.027

Shabani, M., Tran, D. T., Magris, M., Kanniainen, J. & Iosifidis, A. (2022). Multi-head Temporal Attention-Augmented Bilinear Network for Financial time series prediction. In 30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings (pp. 1487-1491). IEEE. https://doi.org/10.23919/EUSIPCO55093.2022.9909957

Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2021). Multi-Exit Vision Transformer for Dynamic Inference. In The 32nd British Machine Vision Conference https://www.semanticscholar.org/paper/Multi-Exit-Vision-Transformer-for-Dynamic-Inference-Bakhtiarnia-Zhang/26f61039857423c0aad2c44f0e7769cbb61246c9

Iosifidis, A., Tefas, A. & Pitas, I. (2012). Multidimensional Sequence Classification based on Fuzzy Distances and Discriminant Analysis. IEEE Transactions on Knowledge and Data Engineering, 25(11), 2564-2575. https://doi.org/10.1109/TKDE.2012.223

Iosifidis, A. & Gabbouj, M. (2016). Multi-class Support Vector Machine Classifiers using Intrinsic and Penalty Graphs. Pattern Recognition, 55, 231-246. https://doi.org/10.1016/j.patcog.2016.02.002

Bahner , K., Larsen, J. J. & Auken, E. (2015). Multichannel magnetic resonance sounding with wirelessly operated coils – A design study. Poster session presented at The 6th International Workshop on Magnetic Resonance, Aarhus , Denmark. http://hgg.au.dk/fileadmin/www.dna18.au.dk/MRS2015_program.pdf

Nyholm Jørgensen, R. & Nørremark, M. (2015). Muligheder og perspektiver i anvendelse af robotter i roer, gulerødder og kartofler. Abstract from Plantekongres 2015, Herning, Denmark.

Gislum, R., Nyholm Jørgensen, R. & Mortensen, A. K. (2015). Mulige gevinster ved gradueret gødskning på basis af droneoptagelser. Abstract from Plantekongres 2015, Herning, Denmark.

Kraus, T., Ferreau, H. J., Kayacan, E., Ramon, H., De Baerdemaeker, J., Diehl, M. & Saeys, W. (2013). Moving horizon estimation and nonlinear model predictive control for autonomous agricultural vehicles. Computers and Electronics in Agriculture, 98, 25-33. https://doi.org/10.1016/j.compag.2013.06.009

Iosifidis, A., Nikolaidis, N. & Pitas, I. (2010). Movement recognition exploiting multi-view information. In Multimedia Signal Processing (MMSP), 2010 IEEE International Workshop on (pp. 427-431). IEEE. https://doi.org/10.1109/MMSP.2010.5662059

Sadiq, M. T., Yu, X., Yuan, Z., Aziz, M. Z., Rehman, N. U., Ding, W. & Xiao, G. (2022). Motor Imagery BCI Classification Based on Multivariate Variational Mode Decomposition. IEEE Transactions on Emerging Topics in Computational Intelligence, 6(5), 1177-1189. Advance online publication. https://doi.org/10.1109/tetci.2022.3147030

Kristensen, M. V., Ahrendt, P., Lindballe, T. B., Nielsen, O. H. A., Kylling, A. P., Karstoft, H., Imparato, A., Rigau, L. H., Stadler, B., Stapelfeldt, H. & Keiding, S. R. (2012). Motion analysis of optically trapped particles and cells using 2D Fourier analysis. Optics Express, 20(3), 1953-1962. https://doi.org/10.1364/OE.20.001953

Wang, Z., Chen, L., Chen, H. & Rehman, N. U. (2023). Monthly ship price forecasting based on multivariate variational mode decomposition. Engineering Applications of Artificial Intelligence, 125, Article 106698. https://doi.org/10.1016/j.engappai.2023.106698

Laakom, F., Raitoharju, J., Iosifidis, A., Nikkanen, J. & Gabbouj, M. (2021). Monte Carlo Dropout Ensembles for Robust Illumination Estimation. In IJCNN 2021 - International Joint Conference on Neural Networks, Proceedings IEEE. https://doi.org/10.1109/IJCNN52387.2021.9534314

Green, O., Shahrak Nadimi, E., Blanes-Vidal, V., Jørgensen, R. N., Storm, I. M. L. D. & Sørensen, C. A. G. (2009). Monitoring and Modeling Temperature Variations Inside Silage Stack Using Novel Wireless Sensor Networks. Computers and Electronics in Agriculture, 69(2), 149-157.

S. Nadimi, E., Jørgensen, R. N., Blanes-Vidal, V. & Christensen, S. (2012). Monitoring and classifying animal behavior using ZigBee-based mobile ad hoc wireless sensor networks and artificial neural networks. Computers and Electronics in Agriculture, 82, 44-54. https://doi.org/10.1016/j.compag.2011.12.008

Midtiby, H., Laursen, M. S., Jørgensen, R. N. & Krüger, N. (2012). MODICOVI - Monocot and dicot coverage ratio vision based method for real time estimation of canopy coverage ratio between cereal and dicotyledon weeds.

Shahrak Nadimi, E. & Jørgensen, R. N. (2012). MoDest GrassUp. (Patent No. DK2010/050334).

Jørgensen, R. N. & S. Nadimi, E. (2010, Feb 1). MoDest GrassUp.

Kayacan, E., Kayacan, E., Ramon, H. & Saeys, W. (2012). Model Predictive Control of the Yaw Dynamics of an Autonomous Tractor. In A. Peruzzi (Ed.), : Proceedings of the First International Conference on Robotics and Associated High-technologies and Equipment for Agriculture. Applications of automated systems and robotics for crop protection in sustainable precision agriculture (pp. 157-162). University of Pisa.

Eren, U., Prach, A., Bahadir Kocer, B., Rakovic, S. V., Kayacan, E. & Acikmese, B. (2017). Model Predictive Control in Aerospace Systems: Current State and Opportunities. AIAA Journal of Guidance, Control and Dynamics, 40(7), 1541-1566. https://doi.org/10.2514/1.G002507

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

Christensen, L. K., Bennedsen, B. S., Jørgensen, R. & Nielsen, H. (2004). Modelling nitrogen and phosphorus content at early growth stages in spring barley using spectral line scanning. Biosystems Engineering, 88(1), 19-24.

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Revised 10.08.2023

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