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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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, Article 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 from ESHRE, Vienna, Austria. https://www.eshre.eu/ESHRE2019/Programme/Searchable#!abstractdetails/0000573820

Magris, M. (2019). A vine copula extension for the HAR model. https://arxiv.org/pdf/1907.08522.pdf

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, No. 2019-760-001283, 3 p., Jul 03, 2019.

Passalis, N., Tefas, A., Iosifidis, A. & Gabbouj, M. (2019). Class-based Variational Representation Learning for Robust Image Retrieval. In 2019 IEEE International Conference on Image Processing, ICIP 2019 - Proceedings (pp. 854-858). Article 8802945 IEEE. https://doi.org/10.1109/ICIP.2019.8802945

Laakom, F., Raitoharju, J., Iosifidis, A., Nikkanen, J. & Gabbouj, M. (2019). Color Constancy Convolutional Autoencoder. (pp. 1085-1090). https://arxiv.org/abs/1906.01340

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

Panagiotatos, G., Passalis, N., Iosifidis, A., Gabbouj, M. & Tefas, A. (2019). Curriculum-based Teacher Ensemble for Robust Neural Network Distilation. In 27th European Signal Processing Conference EUSIPCO 2019 IEEE. http://eusipco2019.org/Proceedings/papertitles.html

Panagiotatos, G., Passalis, N., Iosifidis, A., Gabbouj, M. & Tefas, A. (2019). Curriculum-based teacher ensemble for robust neural network distillation. In 2019 27th European Signal Processing Conference (EUSIPCO) IEEE. https://doi.org/10.23919/EUSIPCO.2019.8903112

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

Thanh Tran, D., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2019). Data-driven Neural Architecture Learning for Financial Time-series Forecasting. In Digital Image and Signal Processing https://arxiv.org/ftp/arxiv/papers/1903/1903.06751.pdf

Passalis, N., Tefas, A., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2019). Deep Adaptive Input Normalization for Time Series Forecasting. arXiv.org. https://arxiv.org/pdf/1902.07892.pdf

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

Passalis, N., Tefas, A., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2019). Deep Temporal Logistic Bag-of-features for Forecasting High Frequency Limit Order Book Time Series. In 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings (pp. 7545-7549). Article 8682297 IEEE. https://doi.org/10.1109/ICASSP.2019.8682297

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), Article 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. In J. V. Stafford (Ed.), Precision Agriculture '19 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019 (pp. 959-965). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-888-9_118

Wang, H., Mortensen, A. K., Mao, P., Boelt, B. & Gislum, R. (2019). Estimating the nitrogen nutrition index in grass seed crops using a UAV-mounted multispectralcamera. International Journal of Remote Sensing, 40(7), 2467-2482. https://doi.org/10.1080/01431161.2019.1569783

Ntakaris, A., Mirone, G., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2019). Feature Engineering for Mid-Price Prediction with Deep Learning. IEEE Access, 7, 82390 - 82412. Article 8743410. https://doi.org/10.1109/ACCESS.2019.2924353

Makinen, Y., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2019). Forecasting jump arrivals in stock prices: new attention-based network architecture using limit order book data. Quantitative Finance, 19(12), 2033-2050 . Advance online publication. https://doi.org/10.1080/14697688.2019.1634277

Mäkinen, M., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2019). Forecasting of Jump Arrivals in Stock Prices: New Attention-based Network Architecture using Limit Order Book Data. arXiv.org. https://arxiv.org/pdf/1810.10845.pdf

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

Sarabakha, A., Fu, C. & Kayacan, E. (2019). Intuit before tuning: Type-1 and type-2 fuzzy logic controllers. Applied Soft Computing Journal, 81, Article 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. In 2019 18th European Control Conference, ECC 2019 Article 8796140 IEEE. https://doi.org/10.23919/ECC.2019.8796140

Thanh Tran, D., Kiranyaz, S., Gabbouj, M. & Iosifidis, A. (2019). Knowledge Transfer For Face Verification Using Heterogeneous Generalized Operational Perceptrons. In 2019 IEEE International Conference on Image Processing (ICIP) (pp. 1168-1172). Article 8804296 IEEE. https://doi.org/10.1109/ICIP.2019.8804296

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. In S. V. Rakovic & W. Levine (Eds.), Handbook of Model Predictive Control (1 ed., pp. 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. In 2019 IEEE International Conference on Fuzzy Systems, FUZZ 2019 Article 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

Tran, D. T. & Iosifidis, A. (2019). Learning to Rank: A Progressive Neural Network Learning Approach. In 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings (pp. 8355-8359). Article 8683711 IEEE. https://doi.org/10.1109/ICASSP.2019.8683711

Tzogka, C., Passalis, N., Iosifidis, A., Gabbouj, M. & Tefas, A. (2019). Less is more: Deep Learning using subjective annotations for sentiment analysis from social media. In 2019 IEEE 29th International Workshop on Machine Learning for Signal Processing, MLSP 2019: Proceedings Article 8918792 IEEE. https://doi.org/10.1109/MLSP.2019.8918792

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. (Ed.) & Pedersen, C. F. (Ed.) (2019). LoRa and LoRaWAN Case Studies. European Regional Development Fund and Central Denmark Region.

Nousi, P., Tsantekidis, A., Passalis, N., Ntakaris, A., Kanniainen, J., Tefas, A., Gabbouj, M. & Iosifidis, A. (2019). Machine Learning for Forecasting Mid Price Movement using Limit Order Book Data. IEEE Access, 7, 64722 - 64736 . Article 8713851. https://doi.org/10.1109/ACCESS.2019.2916793

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. In J. V. Stafford (Ed.), Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019 (pp. 231-237). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-888-9_28

Gautam, C., Tiwari, A. & Iosifidis, A. (2019). Minimum Variance-Embedded Multi-layer Kernel Ridge Regression for One-class Classification. In S. Sundaram (Ed.), Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018 (pp. 389-396). Article 8628692 IEEE. https://doi.org/10.1109/SSCI.2018.8628692

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

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. In O. Huguenin-Elie, B. Studer, R. Kölliker, D. Reheul, M. Probo, P. Barre, U. Feuerstein, I. Roldan-Ruiz, P. Mariotte & A. Hopkins (Eds.), 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 (pp. 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. In 2019 International Conference on Robotics and Automation, ICRA 2019 (pp. 7727-7733). Article 8794314 IEEE. https://doi.org/10.1109/ICRA.2019.8794314

Magris, M. (2019). On the simulation of the Hawkes process via Lambert-W functions. arXiv. https://arxiv.org/abs/1907.09162

Camci, E. & Kayacan, E. (2019). Planning swift maneuvers of quadcopter using motion primitives explored by reinforcement learning. In Proceedings of the American Control Conference: 2019 American Control Conference, ACC 2019 (pp. 279-285). Article 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. Article 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

Tran, D. T., Kiranyaz, S., Gabbouj, M. & Iosifidis, A. (2019). PyGOP: A Python library for Generalized Operational Perceptron algorithms. Knowledge-Based Systems, 182, Article 104801. https://doi.org/10.1016/j.knosys.2019.06.009

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. Advance online publication. https://doi.org/10.1109/TASE.2018.2829927

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

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

Nyholm Jørgensen, R. (Producer). (2019). RoboWeedMaps - Walking the weed maps with your mobile phone. Pictures, Video and sound recordings (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. 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

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

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