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

Passalis, N., Tefas, A., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2020). Temporal Bag-of-Features Learning for Predicting Mid Price Movements using High Frequency Limit Order Book Data. IEEE Transactions on Emerging Topics in Computational Intelligence, 4(6), 774-785. https://doi.org/10.1109/TETCI.2018.2872598

Thanh Tran, D., Kiranyaz, S., Gabbouj, M. & Iosifidis, A. (2020). Heterogeneous Multilayer Generalized Operational Perceptron. IEEE Transactions on Neural Networks and Learning Systems, 31(3), 710-724. Artikel 8727718. https://doi.org/10.1109/TNNLS.2019.2914082

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 . Artikel 8713851. https://doi.org/10.1109/ACCESS.2019.2916793

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

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. Artikel 8743410. https://doi.org/10.1109/ACCESS.2019.2924353

Cao, G., Iosifidis, A., Gabbouj, M., Raghavan, V. & Gottumukkala, R. (2021). Deep Multi-view Learning to Rank. IEEE Transactions on Knowledge and Data Engineering, 33(4), 1426-1438. Artikel 8845659. https://doi.org/10.1109/TKDE.2019.2942590

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

Thanh Tran, D., Kiranyaz, S., Gabbouj, M. & Iosifidis, A. (2020). Progressive Operational Perceptrons with Memory. Neurocomputing, 379, 172-181. https://doi.org/10.1016/j.neucom.2019.10.079

Hansen, O. L. P., Svenning, J.-C., Olsen, K., Dupont, S., Garner, B. H., Iosifidis, A., Price, B. W. & Høye, T. T. (2019). Image data used for publication "Species-level image classification with convolutional neural network enable insect identification from habitus images". Datasæt https://doi.org/10.5281/zenodo.3549369

Passalis, N., Iosifidis, A., Gabbouj, M. & Tefas, A. (2020). Variance-preserving Deep Metric Learning for Content-based Image Retrieval. Pattern Recognition Letters, 131, 8-14. https://doi.org/10.1016/j.patrec.2019.11.041

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). 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.

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

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

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

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

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

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

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

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

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

Govdeli, Y., Moheed Bin Muzaffar, S., Raj, R., Elhadidi, B. & Kayacan, E. (2019). Unsteady aerodynamic modeling and control of pusher and tilt-rotor quadplane configurations. Aerospace Science and Technology, 94, Artikel 105421. https://doi.org/10.1016/j.ast.2019.105421

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

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

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

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

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

Hussain, S., Qi, C., Asif, M. R. & Sohrab Khan, M. (2016). Active Contours for image segmentation using complex domain-based approach. IET Image Processing, 10(2), 121-129. https://doi.org/10.1049/iet-ipr.2014.0730

Karim, S., Zhang, Y., Asif, M. R. & Ali, S. (2017). Comparative analysis of feature extraction methods in satellite imagery. Journal of Applied Remote Sensing, 11(4), Artikel 042618. https://doi.org/10.1117/1.JRS.11.042618

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

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

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

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

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 . https://doi.org/10.1080/14697688.2019.1634277

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

Christiansen, P. H., Kragh, M. F., Brodskiy, Y. & Karstoft, H. (2019). UnsuperPoint: End-to-end Unsupervised Interest Point Detector and Descriptor. arxiv.org. https://arxiv.org/abs/1907.04011

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

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.

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. Poster session præsenteret på IEEE Conference on Computer Vision and Pattern Recognition 2019, Long Beach, California, USA.

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. I The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops IEEE. http://openaccess.thecvf.com/content_CVPRW_2019/html/CVPPP/Skovsen_The_GrassClover_Image_Dataset_for_Semantic_and_Hierarchical_Species_Understanding_CVPRW_2019_paper.html

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

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. I 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings (s. 7545-7549). Artikel 8682297 IEEE. https://doi.org/10.1109/ICASSP.2019.8682297

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

Mortensen, A. K., Skovsen, S., Karstoft, H. & Gislum, R. (2019). The Oil Radish Growth Dataset. Datasæt

Mortensen, A. K., Skovsen, S., Karstoft, H. & Gislum, R. (2019). The Oil Radish Growth Dataset for Semantic Segmentation and Yield Estimation. Poster session præsenteret på IEEE Conference on Computer Vision and Pattern Recognition 2019, Long Beach, California, USA.

Mortensen, A. K., Skovsen, S., Karstoft, H. & Gislum, R. (2019). The Oil Radish Growth Dataset for Semantic Segmentation and Yield Estimation. I Proceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019 (s. 2703-2710). Artikel 9025602 IEEE. https://doi.org/10.1109/CVPRW.2019.00328

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.

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Revideret 10.08.2023

AU Engineering