Find

For students
For PhDs
For employees

Department of Electrical and Computer Engineering

Publications

Sort by: Date | Author | Title

Oleksiienko, I. & Iosifidis, A. (2022). 3D object detection and tracking. In A. Iosifidis & A. Tefa (Eds.), Deep Learning for Robot Perception and Cognition (pp. 313-340). Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00018-X

Malik, J., Kiranyaz, S., Al-Raoush, R. I., Monga, O., Garnier, P., Foufou, S., Bouras, A., Iosifidis, A., Gabbouj, M. & Baveye, P. C. (2022). 3D Quantum Cuts for Automatic Segmentation of Porous Media in Tomography Images. Computers & Geosciences, 159, Article 105017. https://doi.org/10.1016/j.cageo.2021.105017

Iosifidis, A. & Gabbouj, M. (2015). A Bayesian Approach for Extreme Learning Machine-based Subspace Learning. In Signal Processing Conference (EUSIPCO), 2015 23rd European (pp. 2356-2360). IEEE. https://doi.org/10.1109/EUSIPCO.2015.7362806

Muravev, A., Thanh Tran, D., Iosifidis, A., Kiranyaz, S. & Gabbouj, M. (2018). Acceleration approaches for big data analysis. In 2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings: Proceedings (pp. 311-315). Article 8451082 IEEE. https://doi.org/10.1109/ICIP.2018.8451082

Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2024). ACCURATE GIGAPIXEL CROWD COUNTING BY ITERATIVE ZOOMING AND REFINEMENT. In ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 6510-6514). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP48485.2024.10446065

Iosifidis, A., Tefas, A. & Pitas, I. (2013). Active Classification for Human Action Recognition. In Image Processing (ICIP), 2013 20th IEEE International Conference on (pp. 3249-3253). IEEE. https://doi.org/10.1109/ICIP.2013.6738669

Iosifidis, A., Tefas, A. & Pitas, I. (2011). Activity based Person Identification using Fuzzy Representation and Discriminant Learning. IEEE Transactions on Information Forensics and Security, 7(2), 530-542. https://doi.org/10.1109/TIFS.2011.2175921

Passalis, N., Tefas, A., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2020). Adaptive Normalization for Forecasting Limit Order Book Data Using Convolutional Neural Networks. In 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings (pp. 1713-1717). Article 9054321 IEEE. https://doi.org/10.1109/ICASSP40776.2020.9054321

Iosifidis, A., Mouroutsos, S. G. & Gasteratos, A. (2011). A hybrid static/active video surveillance system. International Journal of Optomechatronics, 5(1), 80-95. https://doi.org/10.1080/15599612.2011.553252

Magris, M., Ntakaris, A., Kanniainen, J., Iosifidis, A. & Gabbouj, M. (2016). Analysis of high-frequency order flow dynamics with machine learning techniques. In 10th International Conference on Computational and Financial Econometrics

Bakhtiarnia, A., Leporowski, B., Esterle, L. & Iosifidis, A. (2022). Analysis of the Effect of Low-Overhead Lossy Image Compression on the Performance of Visual Crowd Counting for Smart City Applications. In 2022 IEEE International Smart Cities Conference (ISC2) IEEE. https://doi.org/10.1109/ISC255366.2022.9921939

Oleksiienko, I. & Iosifidis, A. (2021). Analysis of voxel-based 3D object detection methods efficiency for real-time embedded systems. In N. Mallenahalli, A. Bhattacharya, S. Senatore, A. Negi & A. Hirose (Eds.), 2021 International Conference on Emerging Techniques in Computational Intelligence (ICETCI) (pp. 59-64). IEEE. https://doi.org/10.1109/ICETCI51973.2021.9574075

Magris, M. & Iosifidis, A. (2021). Approximate Bayes factors for unit root testing. Paper presented at International Association for Applied Econometrics Annual Conference 2021, Rotterdam, Netherlands. https://www.researchgate.net/publication/349492007_Approximate_Bayes_factors_for_unit_root_testing

Iosifidis, A., Tefas, A. & Pitas, I. (2016). Approximate Kernel Extreme Learning Machine for Large-Scale Data Classification. Neurocomputing, 219, 210-220. https://doi.org/10.1016/j.neucom.2016.09.023

Iosifidis, A., Tefas, A., Pitas, I. & Gabbouj, M. (2016). A review of approximate methods for kernel-based Big Media Data Analysis. In 2016 24th European Signal Processing Conference, EUSIPCO 2016 (pp. 1113-1117). Article 7760421 IEEE. https://doi.org/10.1109/EUSIPCO.2016.7760421

Böttjer, T., Tola, D., Kakavandi, F., Wewer, C. R., Ramanujan, D., Gomes, C., Larsen, P. G. & Iosifidis, A. (2023). A review of unit level digital twin applications in the manufacturing industry. CIRP Journal of Manufacturing Science and Technology, 45, 162-189. https://doi.org/10.1016/j.cirpj.2023.06.011

Jensen, R. I. T., Ferwerda, J., Jørgensen, K. S., Jensen, E. R., Borg, M., Krogh, M. P., Jensen, J. B. & Iosifidis, A. (2023). A synthetic data set to benchmark anti-money laundering methods. Scientific Data, 10(1), Article 661. https://doi.org/10.1038/s41597-023-02569-2

Li, N., Iosifidis, A. & Zhang, Q. (2023). Attention-Based Feature Compression for CNN Inference Offloading in Edge Computing. In M. Zorzi, M. Tao & W. Saad (Eds.), ICC 2023 - IEEE International Conference on Communications (pp. 967-972). IEEE. https://doi.org/10.1109/ICC45041.2023.10279110

Tran, D. T., Passalis, N., Tefas, A., Gabbouj, M. & Iosifidis, A. (2022). Attention-Based Neural Bag-of-Features Learning for Sequence Data. IEEE Access, 10, 45542-45552. https://doi.org/10.1109/ACCESS.2022.3169776

Shabani, M., Tran, D. T., Kanniainen, J. & Iosifidis, A. (2023). Augmented bilinear network for incremental multi-stock time-series classification. Pattern Recognition, 141, Article 109604. https://doi.org/10.1016/j.patcog.2023.109604

Thanh Tran, D., Høye, T. T., Gabbouj, M. & Iosifidis, A. (2018). Automatic Flower and Visitor Detection System. Proceedings of the European Signal Processing Conference, 2018, 405-409. https://doi.org/10.23919/EUSIPCO.2018.8553494

Ärje, J., Milioris, D., Tran, D. T., Jepsen, J. U., Raitoharju, J., Gabbouj, M., Iosifidis, A. & Høye, T. T. (2019). Automatic Flower Detection and Classification System Uing a Light-Weight Convolutional Neural Network. In 27th European Signal Processing Conference EUSIPCO 2019 IEEE. http://eusipco2019.org/Proceedings/papertitles.html

Mann, H. M. R., Iosifidis, A., Jepsen, J. U., Welker, J. M., Loonen, M. J. J. E. & Høye, T. T. (2022). Automatic flower detection and phenology monitoring using time-lapse cameras and deep learning. Remote Sensing in Ecology and Conservation, 8(6), 765-777. https://doi.org/10.1002/rse2.275

Ärje, J., Melvad, C., Jeppesen, M. R., Madsen, S. A., Raitoharju, J., Rasmussen, M. S., Iosifidis, A., Tirronen, V., Gabbouj, M., Meissner, K. & Høye, T. T. (2020). Automatic image-based identification and biomass estimation of invertebrates. Methods in Ecology and Evolution, 11(8), 922-931. https://doi.org/10.1111/2041-210X.13428

Seker, M., Männistö, A., Iosifidis, A. & Raitoharju, J. (2021). Automatic Main Character Recognition for Photographic Studies. In IEEE 23rd International Workshop on Multimedia Signal Processing, MMSP 2021 IEEE. https://doi.org/10.1109/MMSP53017.2021.9733624

Laakom, F., Passalis, N., Raitoharju, J., Nikkanen, J., Tefas, A., Iosifidis, A. & Gabbouj, M. (2020). Bag of Color Features for Color Constancy. IEEE Transactions on Image Processing, 29, 7722-7734. Article 9130881. https://doi.org/10.1109/TIP.2020.3004921

Magris, M., Shabani, M. & Iosifidis, A. (2023). Bayesian bilinear neural network for predicting the mid-price dynamics in limit-order book markets. Journal of Forecasting, 42(6), 1407-1428. https://doi.org/10.1002/for.2955

Magris, M. & Iosifidis, A. (2023). Bayesian learning for neural networks: an algorithmic survey. Artificial Intelligence Review, 56(10), 11773-11823. https://doi.org/10.1007/s10462-023-10443-1

Raitoharju, J., Riabchenko, E., Ahmad, I., Iosifidis, A., Gabbouj, M., Kiranyaz, S., Tirronen, V., Ärje, J., Kärkkäinen, S. & Meissner, K. (2018). Benchmark Database for Fine-Grained Image Classification of Benthick Macroinvertebrates. Image and Vision Computing, 78, 73-83. https://doi.org/10.1016/j.imavis.2018.06.005

Ntakaris, A., Magris, M., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2018). Benchmark dataset for mid-price forecasting of limit order book data with machine learning methods. Journal of Forecasting, 37(8), 852-866. https://doi.org/10.1002/for.2543

Ntakaris, A., Magris, M., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2017). Benchmark Dataset for Mid-Price Prediction of Limit Order Book data. arXiv. https://arxiv.org/pdf/1705.03233.pdf

Iosifidis, A., Tefas, A., Pitas, I. & Gabbouj, M. (2017). Big Media Data Analysis. Signal Processing: Image Communication, 59, 105-108. https://doi.org/10.1016/j.image.2017.10.004

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

Iosifidis, A. (2020). Class mean vector component and discriminant analysis. Pattern Recognition Letters, 140, 207-213. https://doi.org/10.1016/j.patrec.2020.10.014

Iosifidis, A. & Gabbouj, M. (2017). Class-Specific Kernel Discriminant Analysis based on Cholesky Decomposition. In 2017 International Joint Conference on Neural Networks, IJCNN 2017 - Proceedings (pp. 1141-1146). Article 7965980 IEEE. https://doi.org/10.1109/IJCNN.2017.7965980

Iosifidis, A. & Gabbouj, M. (2017). Class-Specific Kernel Discriminant Analysis revisited: further analysis and extensions. IEEE Transactions on Cybernetics, 47(12), 4485-4496. Article 7590015. https://doi.org/10.1109/TCYB.2016.2612479

Iosifidis, A., Gabbouj, M. & Pekki, P. (2015). Class-specific nonlinear projections using class-specific kernel spaces. In Trustcom/BigDataSE/ISPA, 2015 IEEE (pp. 17-24). IEEE. https://doi.org/10.1109/Trustcom.2015.557

Iosifidis, A., Tefas, A. & Pitas, I. (2015). Class-specific nonlinear subspace learning based on optimized class representation. In Signal Processing Conference (EUSIPCO), 2015 23rd European (pp. 2491-2495). IEEE. https://doi.org/10.1109/EUSIPCO.2015.7362833

Iosifidis, A., Tefas, A. & Pitas, I. (2015). Class-specific Reference Discriminant Analysis with application in Human Behavior Analysis. IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS, 45(3), 315-326. https://doi.org/10.1109/THMS.2014.2379274

Rafiei Foroushani, M. & Iosifidis, A. (2023). Class-Specific Variational Auto-Encoder for Content-Based Image Retrieval. In 2023 International Joint Conference on Neural Networks (IJCNN) IEEE. https://doi.org/10.1109/IJCNN54540.2023.10191068

Nielsen, A. H., Iosifidis, A. & Karstoft, H. (2020). CloudCast: A Satellite-Based Dataset and Baseline for Forecasting Clouds. Abstract from European Conference on Computer Vision Workshop . https://drive.google.com/file/d/1_TV20JCIyBaetN6Y1mt7K5FeMx431Rr3/view

Nielsen, A. H., Iosifidis, A. & Karstoft, H. (2021). CloudCast: A Satellite-Based Dataset and Baseline for Forecasting Clouds. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 3485-3494. Article 9366908. https://doi.org/10.1109/JSTARS.2021.3062936

Nielsen, A. H., Wagner, A., Iosifidis, A. & Karstoft, H. (2020). Cloud Nowcasting on Satellite Images: A Novel Dataset and Experimental Comparisons. https://ams.confex.com/ams/2020Annual/meetingapp.cgi/Paper/365696

Waris, M. A., Iosifidis, A. & Gabbouj, M. (2017). CNN-based Edge Filtering for Object Proposals. Neurocomputing, 266, 631-640. https://doi.org/10.1016/j.neucom.2017.05.071

Li, N., Iosifidis, A. & Zhang, Q. (2022). Collaborative edge computing for distributed CNN inference acceleration using receptive field-based segmentation. Computer Networks, 214, Article 109150. https://doi.org/10.1016/j.comnet.2022.109150

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

Iosifidis, A. & Gabbouj, M. (2016). Combining Multi-class Maximum Margin Classification with Linear Discriminant Analysis for Human Action Recognition. In 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings (pp. 4180-4184). Article 7533147 IEEE. https://doi.org/10.1109/ICIP.2016.7533147

Iosifidis, A., Tefas, A. & Pitas, I. (2014). Computational Intelligence Approaches for Digital Media Analysis and Description. In J.-S. Pan, V. Snasel, E. S. Corchado, A. Abraham & S.-L. Wang (Eds.), Intelligent Data analysis and its Applications, Volume II (Vol. 2, pp. 263-272). Springer. https://doi.org/10.1007/978-3-319-07773-4_26

Iosifidis, A. (2013). Computer Vision and Pattern Recognition Techniques for Human-Computer Interaction.

Rafiei Foroushani, M., Raitoharju, J. & Iosifidis, A. (2023). Computer Vision on X-Ray Data in Industrial Production and Security Applications: A Comprehensive Survey. IEEE Access, 11, 2445 - 2477. https://doi.org/10.1109/ACCESS.2023.3234187

Displaying results 1 to 50 out of 290

1

Revised 10.08.2023

-

Alexandros Iosifidis