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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Christensen, L. K. & Jørgensen, R. (2003). Spatial reflectance at sub-leaf scale discriminating NPK stress in barley. In Proc. 4th ECPA and 1st ECPLF, Berlin, Germany (pp. 622-622). Wageningen Academic Publishers.

Christensen, L. K. & Jørgensen, R. (2003). Spatial Reflectance at Sub-Leaf Scale Discriminating NPK Stress Characteristics in Barley Using Multiway Partial Least Squares Regression. Paper presented at ASAE Annual International Meeting, Las Vegas, United States. http://asae.frymulti.com/request.asp?JID=5&AID=13744&CID=lnv2003&T=2

Farkhani, S., Kragh, M. F., Christiansen, P. H., Nyholm Jørgensen, R. & Karstoft, H. (2019). Sparse-to-Dense Depth Completion in Precision Farming. In 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 Article 35 Association for Computing Machinery. https://doi.org/10.1145/3387168.3387230

Pedersen, C. F. & Bäckström, T. (2014). Sparse Time-Frequency Representation of Speech by the Vandermonde Transform. In Proceedings of the Annual Conference of the International Speech Communication Association: INTERSPEECH 2014 (pp. 2248-2252)

Iosifidis, A., Tefas, A. & Pitas, I. (2015). Sparse Extreme Learning Machine classifier exploiting Intrinsic Graphs. Pattern Recognition Letters, 65, 192-196. https://doi.org/10.1016/j.patrec.2015.07.036

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

Ahmadieh Khanesar, M., Kayacan, E., Kaynak, O. & Saeys, W. (2013). Sliding Mode Type-2 Fuzzy Control of Robotic Arm Using Ellipsoidal Membership Functions. In Control Conference (ASCC), 2013 9th Asian (pp. 1-6). IEEE. https://doi.org/10.1109/ASCC.2013.6606393

Kayacan, E. & Kaynak, O. (2012). Sliding Mode Control Theory-based Algorithm for Online Learning in Type-2 Fuzzy Neural Networks: Application to Velocity Control of an Electro Hydraulic Servo System. INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 26(7), 645-659. https://doi.org/10.1002/acs.1292

Rubio Hervas, J., Kayacan, E., Reyhanoglu, M. & Tang, H. (2014). Sliding Mode Control of Fixed- Wing UAVs in Windy Environments. In Control Automation Robotics & Vision (ICARCV), 2014 13th International Conference on (pp. 986-991). IEEE . https://doi.org/10.1109/ICARCV.2014.7064440

Kayacan, E., Cigdem, O. & Kaynak, O. (2011). Sliding Mode Control Approach for Online Learning as Applied to Type-2 Fuzzy Neural Networks and its Experimental Evaluation. IEEE Transactions on Industrial Electronics, 59(9), 3510-3520. https://doi.org/10.1109/TIE.2011.2182017

Lati, R. N., Rasmussen, J., Andujar, D., Dorado, J., Berge, T. W., Wellhausen, C., Pflanz, M., Nordmeyer, H., Schirrmann, M., Eizenberg, H., Neve, P., Jørgensen, R. N. & Christensen, S. (2021). Site-specific weed management—constraints and opportunities for the weed research community: Insights from a workshop. Weed Research, 61(3), 147-153. https://doi.org/10.1111/wre.12469

Christensen, S., Søgaard, H. T., Kudsk, P., Nørremark, M., Lund, I., Shahrak Nadimi, E. & Jørgensen, R. N. (2009). Site-specific weed control technologies. Weed Research, 49, 233-241. https://doi.org/10.1111/j.1365-3180.2009.00696.x

Kayacan, E. & Kaynak, O. (2011). Single-step Ahead Prediction Based on the Principle of Concatenation Using Grey Predictors. Expert Systems with Applications, 38(8), 9499-9505. https://doi.org/10.1016/j.eswa.2011.01.143

Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2022). Single-layer vision transformers for more accurate early exits with less overhead. Neural Networks, 153, 461-473. https://doi.org/10.1016/j.neunet.2022.06.038

Iosifidis, A., Tefas, A. & Pitas, I. (2015). Single-hidden Layer Feedforward Neural network training using class geometric information. In Lecture Notes: Studies in Computational Intelligence Springer.

Cros, O., Volden, M., Flaaris, J. J., Brix, L. C., Pedersen, C. F., Hansen, K. V., Larsen, O. V., Østergaard, L. R. & Haase, J. (2002). Simulating the puncture of the human ventricle. In 10th Annual Medicine Meets Virtual Reality (MMVR) Conference, Digital upgrades: Applying Moore's Law to health

Oniz, Y., Kayacan, E. & Kaynak, O. (2008). Simulated and Experimental Study of Antilock Braking System Using Grey Sliding Mode Control. In Systems, Man and Cybernetics, 2007. ISIC. IEEE International Conference on (pp. 90-95). IEEE . https://doi.org/10.1109/ICSMC.2007.4413975

Ugurlu, H. I., Pham, X. H. & Kayacan, E. (2022). Sim-to-Real Deep Reinforcement Learning for Safe End-to-End Planning of Aerial Robots. Robotics, 11(5), Article 109. https://doi.org/10.3390/robotics11050109

Fu, C., Sarabakha, A., Kayacan, E., Wagner, C., John, R. & Garibaldi, J. M. (2017). Similarity-based Non-Singleton Fuzzy Logic Control for Improved Uncertainty Handling in Quadrotor UAVs. In Fuzzy Systems (FUZZ-IEEE), 2017 IEEE International Conference on (pp. 1-6). IEEE. https://doi.org/10.1109/FUZZ-IEEE.2017.8015440

Nielsen, L., Olesen, C. R., Nyholm Jørgensen, R. & Fris, H. J. (2015). Sikring af levesteder på engarealer med biomassehøst i kombination med vildthensyn. Poster session presented at Biodiversitetssymposiet 2015, Aarhus , Denmark.

Nielsen, L., Olesen, C. R., Nyholm Jørgensen, R. & Fris, H. J. (2015). Sikring af levesteder på engarealer med biomassehøst i kombination med vildthensyn. Abstract from Biodiversitetssymposiet 2015, Aarhus , Denmark.

Liu, L., Grombacher, D., Griffiths, M., Vang, M. & Larsen, J. J. (2023). Signal Processing Steady-State Surface NMR Data. IEEE Transactions on Instrumentation and Measurement, 72, Article 6502313. https://doi.org/10.1109/TIM.2023.3264033

Larsen, J. J. & Vienne, G. (2004). Side pumping of double-clad photonic crystal fibers. Optics Letters, 29(5), 436-438. https://doi.org/10.1364/OL.29.000436

Pedersen, C. F., Andersen, O. & Dalsgaard, P. (2010). Separation of Mixed Phase Signals by Zeros of the Z-transform: A Reformulation of Complex Cepstrum Based Separation by Causality. I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings, 2010(35), 5050-5053. https://doi.org/10.1109/ICASSP.2010.5495060

Skjødt, P., Hansen, P. M., Jørgensen, R. & Nielsen, N. E. (2003). Sensor based nitrogen fertilization in winter wheat levelling out spatial variability in protein content. In Proc. 4th ECPA and 1st ECPLF, Berlin, Germany (pp. 311-311). Wageningen Academic Publishers.

Skjødt, P. & Jørgensen, R. (2003). Sensor based nitrogen fertilization increasing grain protein yield in winter wheat. Risø Report Vol. Risø-R-1389(EN)

Streibig, J. C., Rasmussen, J., Andujar, D., Andreasen, C., Berge, T. W., Chachalis, D., Dittmann, T., Gerhards, R., Giselsson, T. M., Hamouz, P., Jaeger-Hansen, C., Jensen, K., Nyholm Jørgensen, R., Keller, M., Laursen, M., Midtiby, H. S., Nielsen, J., Müller, S., Nordmeyer, H. ... Christensen, S. (2014). Sensor-based assessment of herbicide effects. Weed Research, 54(3), 223–233. https://doi.org/10.1111/wre.12079

Mygdalis, V., Iosifidis, A., Tefas, A. & Pitas, I. (2018). Semi-Supervised Subclass Support Vector Data Description for Image and Video Classification. Neurocomputing, 278, 51-61. https://doi.org/10.1016/j.neucom.2017.08.028

Iosifidis, A., Tefas, A. & Pitas, I. (2014). Semi-supervised classification of human actions based on Neural Networks. In Pattern Recognition (ICPR), 2014 22nd International Conference on (pp. 1336-1341). IEEE. https://doi.org/10.1109/ICPR.2014.239

Mortensen, A. K., Dyrmann, M., Karstoft, H., Nyholm Jørgensen, R. & Gislum, R. (2016). Semantic Segmentation of Mixed Crops using Deep Convolutional Neural Network. Paper presented at CIGR 2016, World Congress. http://conferences.au.dk/uploads/tx_powermail/biomap_-_cigr_2016_-_paper_-_final.pdf

Chen, Q., Chen, J., Lang, X., Xie, L., Rehman, N. U. & Su, H. (2021). Self-tuning variational mode decomposition. Journal of the Franklin Institute, 358(15), 7825-7862. https://doi.org/10.1016/j.jfranklin.2021.07.021

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

Kiranyaz, S., Malik, J., Abdallah, H. B., Ince, T., Iosifidis, A. & Gabbouj, M. (2021). Self-organized Operational Neural Networks with Generative Neurons. Neural Networks, 140, 294-308. https://doi.org/10.1016/j.neunet.2021.02.028

Tu, G. J., Karstoft, H., Pedersen, L. J. & Jørgensen, E. (2014). Segmentation of sows in farrowing pens. IET Image Processing, 8(1), 56-68. https://doi.org/10.1049/iet-ipr.2012.0734

Mortensen, A. K., Bender, A., Whelan, B., Barbour, M. M., Sukkarieh, S., Karstoft, H. & Gislum, R. (2018). Segmentation of lettuce in coloured 3D point clouds for fresh weight estimation. Computers and Electronics in Agriculture, 154, 373-381. https://doi.org/10.1016/j.compag.2018.09.010

Giselsson, T. M., Midtiby, H. & Jørgensen, R. N. (2013). Seedling Discrimination with Shape Features Derived from a Distance Transform. Sensors, 13(5), 5585. https://doi.org/10.3390/s130505585

Iosifidis, A. & Gabbouj, M. (2016). Scaling up Class-Specific Kernel Discriminant Analysis for large-scale Face Verification. IEEE Transactions on Information Forensics and Security, 11(11), 2453-2465. Article 7494969. https://doi.org/10.1109/TIFS.2016.2582562

Sveistrup, D., Jørgensen, R. N., Green, O., Nørremark, M. & Sørensen, C. A. G. (2010). Satellite, Internet & Computer Aided Trails.

Thanh Tran, D., Waris, M. A., Gabbouj, M. & Iosifidis, A. (2017). Sample-based regularization for Support Vector Machine Classification. In The 7th International Conference on Image Processing, Tools and Applications http://www.cs.tut.fi/~iosifidi/files/conference/2017_IPTA_DropOutSVM.pdf?dl=0

Aytekin, C., Iosifidis, A., Kiranyaz, S. & Gabbouj, M. (2016). Salient Object Segmentation based on Linearly Combined Affinity Graphs. In 2016 23rd International Conference on Pattern Recognition, ICPR 2016 (pp. 3769-3774). Article 7900221 IEEE. https://doi.org/10.1109/ICPR.2016.7900221

Xu, L., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2022). Saliency-based Weighted Multilabel Linear Discriminant Analysis. IEEE Transactions on Cybernetics, 52(10), 10200-10213. https://doi.org/10.1109/TCYB.2021.3069338

le Fevre Sejersen, J., Pimentel De Figueiredo, R. & Kayacan, E. (2021). Safe Vessel Navigation Visually Aided by Autonomous Unmanned Aerial Vehicles in Congested Harbors and Waterways. In 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) (pp. 1901-1907) https://doi.org/10.1109/CASE49439.2021.9551637

Dong, Y., Fu, C. & Kayacan, E. (2016). RRT-based 3D Path Planning for Formation Landing of Quadrotor. In 2016 14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016 (pp. 1-6). Article 7838567 IEEE . https://doi.org/10.1109/ICARCV.2016.7838567

Sørensen, R. A., Nielsen, M. & Karstoft, H. (2020). Routing in congested baggage handling systems using deep reinforcement learning. Integrated Computer-Aided Engineering, 27(2), 139-152. Advance online publication. https://doi.org/10.3233/ICA-190613

Sveistrup, D., Jørgensen, R. N., Nørremark, M., Green, O., Sørensen, C. A. G. & S. Nadimi, E. (2010). RoPDeF - semi-automated and web-based Route Plan Designer of full-scale Field trials for tractor guidance systems. In Conference on Precision Crop Protection (Vol. 3). http://www.precision-crop-protection.uni-bonn.de/gk_conference/abstracts_2010.pdf

Kayacan, E., Kayacan, E., Ramon, H. & Saeys, W. (2014). Robust Tube-based Decentralized Nonlinear Model Predictive Control of an Autonomous Tractor-Trailer System. IEEE - ASME Transactions on Mechatronics, 20(1), 447-456. https://doi.org/10.1109/TMECH.2014.2334612

Mehndiratta, M., Kayacan, E., Reyhanoglu, M. & Kayacan, E. (2020). Robust Tracking Control of Aerial Robots Via a Simple Learning Strategy-Based Feedback Linearization. IEEE Access, 8, 1653-1669. https://doi.org/10.1109/ACCESS.2019.2962512

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, Article 104075. https://doi.org/10.1016/j.dsp.2023.104075

Passalis, N., Iosifidis, A., Gabbouj, M. & Tefas, A. (2021). Robust hypersphere-based weight imprinting for few-shot learning. In 2020 28th European Signal Processing Conference (EUSIPCO (pp. 1392-1396). Article 9287340 IEEE. https://doi.org/10.23919/Eusipco47968.2020.9287340

Chumachenko, K., Iosifidis, A. & Gabbouj, M. (2021). Robust fast subclass discriminant analysis. In 2020 28th European Signal Processing Conference (EUSIPCO) (pp. 1397-1401). Article 9287557 IEEE. https://doi.org/10.23919/Eusipco47968.2020.9287557

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Revised 10.08.2023

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