Publications

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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

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

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

Iosifidis, A. (2020). Danish researchers develop artificial intelligence to expose stock-market fraud. I J. Bruun (red.), Profile 2020 (s. 94-95). Aarhus Universitet, Institut for Ingeniørvidenskab . https://www.e-pages.dk/aarhusuniversitet/2231/html5/

Passalis, N., Tefas, A., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2020). Deep Adaptive Input Normalization for Time Series Forecasting. IEEE Transactions on Neural Networks and Learning Systems, 31(9), 3760-3765. https://doi.org/10.1109/TNNLS.2019.2944933

Iosifidis, A. & Tefas, A. (2020). Deep Learning for Visual Content Analysis. Signal Processing: Image Communication, 83(April), Artikel 115806. https://doi.org/10.1016/j.image.2020.115806

Sohrab, F., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2020). Ellipsoidal Subspace Support Vector Data Description. IEEE Access, 8, 122013-122025. Artikel 9133428. https://doi.org/10.1109/ACCESS.2020.3007123

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

Ärje, J., Raitoharju, J., Iosifidis, A., Tirronen, V., Meissner, K., Gabbouj, M., Kiranyaz, S. & Kärkkäinen, S. (2020). Human experts vs. machines in taxa recognition. Signal Processing: Image Communication, 87, Artikel 115917. https://doi.org/10.1016/j.image.2020.115917

Chumachenko, K., Raitoharju, J., Gabbouj, M. & Iosifidis, A. (2020). Incremental Fast Subclass Discriminant Analysis. I 2020 IEEE International Conference on Image Processing, ICIP 2020 - Proceedings (s. 1771-1775). Artikel 9191328 IEEE. https://doi.org/10.1109/ICIP40778.2020.9191328

Shabani, M. & Iosifidis, A. (2020). Low-Rank Temporal Attention-Augmented Bilinear Network for financial time-series forecasting. I 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 (s. 2156-2161). Artikel 9308440 IEEE. https://doi.org/10.1109/SSCI47803.2020.9308440

Chumachenko, K., Mannisto, A., Iosifidis, A. & Raitoharju, J. (2020). Machine Learning Based Analysis of Finnish World War II Photographers. IEEE Access, 8, 144184-144196. Artikel 9159591. https://doi.org/10.1109/ACCESS.2020.3014458

Ntakaris, A., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2020). Mid-price prediction based on machine learning methods with technical and quantitative indicators. PLOS ONE, 15(6 June), Artikel e0234107. https://doi.org/10.1371/journal.pone.0234107

Kiranyaz, S., Ince, T., Iosifidis, A. & Gabbouj, M. (2020). Operational neural networks. Neural Computing and Applications, 32(11), 6645-6668. https://doi.org/10.1007/s00521-020-04780-3

Tran, D. T., Gabbouj, M. & Iosifidis, A. (2020). Performance Indicator in Multilinear Compressive Learning. I 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 (s. 1822-1828). Artikel 9308418 IEEE. https://doi.org/10.1109/SSCI47803.2020.9308418

Iosifidis, A. (2020). Probabilistic Class-Specific Discriminant Analysis. IEEE Access, 8, 183847-183855. https://doi.org/10.1109/ACCESS.2020.3029514

Laakom, F., Raitoharju, J., Iosifidis, A., Tuna, U., Nikkanen, J. & Gabbouj, M. (2020). Probabilistic Color Constancy. I 2020 IEEE International Conference on Image Processing, ICIP 2020 - Proceedings (s. 978-982). Artikel 9190893 IEEE. https://doi.org/10.1109/ICIP40778.2020.9190893

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

Krestenitis, M., Passalis, N., Iosifidis, A., Gabbouj, M. & Tefas, A. (2020). Recurrent bag-of-features for visual information analysis. Pattern Recognition, 106, Artikel 107380. https://doi.org/10.1016/j.patcog.2020.107380

Hansen, O. L. P., Svenning, J. C., Olsen, K., Dupont, S., Garner, B. H., Iosifidis, A., Price, B. W. & Høye, T. T. (2020). Species-level image classification with convolutional neural network enables insect identification from habitus images. Ecology and Evolution, 10(2), 737-747. https://doi.org/10.1002/ece3.5921

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

Passalis, N., Tefas, A., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2020). Temporal logistic neural Bag-of-Features for financial time series forecasting leveraging limit order book data. Pattern Recognition Letters, 136, 183-189. https://doi.org/10.1016/j.patrec.2020.06.006

Sommer, W. L. & Iosifidis, A. (2020). Text-To-Image Synthesis Method Evaluation Based on Visual Patterns. I 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings (s. 4097-4101). Artikel 9053034 IEEE. https://doi.org/10.1109/ICASSP40776.2020.9053034

Tsantekidis, A., Passalis, N., Tefas, A., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2020). Using Deep Learning for price prediction by exploiting stationary limit order book features. Applied Soft Computing Journal, 93, Artikel 106401. https://doi.org/10.1016/j.asoc.2020.106401

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

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

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

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

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. Artikel 9366908. https://doi.org/10.1109/JSTARS.2021.3062936

Böttjer, T., Ørnskov Rønsch, G., Gonçalves Gomes, C. Â., Ramanujan, D., Iosifidis, A. & Larsen, P. G. (2021). Data-Driven Identification of Remaining Useful Life for Plastic Injection Moulds. I A.-L. Andersen, R. Andersen, D. Brunoe, M. Stoettrup Schioenning Larsen, K. Nielsen, A. Napoleone & S. Kjeldgaard (red.), Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems: Proceedings of the Changeable, Agile, Reconﬁgurable and Virtual Production Conference and the World Mass Customization & Personalization Conference (s. 431-439). Springer. https://www.springerprofessional.de/en/data-driven-identification-of-remaining-useful-life-for-plastic-/19816878

Böttjer, T., Ørnskov Rønsch, G., Gomes, C., Ramanujan, D., Iosifidis, A. & Larsen, P. G. (2021). Data-Driven Identification of Remaining Useful Life for Plastic Injection Moulds. I A.-L. Andersen, R. Andersen, T. D. Brunoe, M. Stoettrup Schioenning Larsen, K. Nielsen, A. Napoleone & S. Kjeldgaard (red.), Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems - Proceedings of the 8th Changeable, Agile, Reconfigurable and Virtual Production Conference CARV 2021 and 10th World Mass Customization and Personalization Conference MCPC 2021 (s. 431-439). Springer. https://doi.org/10.1007/978-3-030-90700-6_49

Høye, T. T., Ärje, J., Bjerge, K., Hansen, O. L. P., Iosifidis, A., Leese, F., Mann, H. M. R., Meissner, K., Melvad, C. & Raitoharju, J. (2021). Deep learning and computer vision will transform entomology. Proceedings of the National Academy of Sciences (PNAS), 118(2), Artikel e2002545117. https://doi.org/10.1073/pnas.2002545117

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

Hvilshøj, F., Iosifidis, A. & Assent, I. (2021). ECINN: Efficient Counterfactuals from Invertible Neural Networks. I 32nd British Machine Vision Conference 2021, BMVC 2021, Virtual https://arxiv.org/abs/2103.13701

Kiranyaz, S., Malik, J., Abdallah, H. B., Ince, T., Iosifidis, A. & Gabbouj, M. (2021). Exploiting heterogeneity in operational neural networks by synaptic plasticity. Neural Computing and Applications, 33(13), 7997-8015. https://doi.org/10.1007/s00521-020-05543-w

Passalis, N., Kanniainen, J., Gabbouj, M., Iosifidis, A. & Tefas, A. (2021). Forecasting Financial Time Series Using Robust Deep Adaptive Input Normalization. Journal of Signal Processing Systems, 93(10), 1235-1251. https://doi.org/10.1007/s11265-020-01624-0

Gautam, C., Tiwari, A., Mishra, P. K., Suresh, S., Iosifidis, A. & Tanveer, M. (2021). Graph-Embedded Multi-Layer Kernel Ridge Regression for One-Class Classification. Cognitive Computation, 13(2), 552-569. https://doi.org/10.1007/s12559-020-09804-7

Tran, D. T., Kanniainen, J. & Iosifidis, A. (2021). How informative is the Order Book Beyond the Best Levels? Machine Learning Perspective. Afhandling præsenteret på NeurIPS 2021 Workshop on Machine Learning meets Econometrics. https://doi.org/10.2139/ssrn.3920827

Passalis, N., Iosifidis, A., Gabbouj, M. & Tefas, A. (2021). Hypersphere-Based Weight Imprinting for Few-Shot Learning on Embedded Devices. IEEE Transactions on Neural Networks and Learning Systems, 32(2), 925-930. https://doi.org/10.1109/TNNLS.2020.2979745

Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2021). Improving the Accuracy of Early Exits in Multi-Exit Architectures via Curriculum Learning. I 2021 International Joint Conference on Neural Networks (IJCNN) IEEE. https://doi.org/10.1109/IJCNN52387.2021.9533875

Laakom, F., Raitoharju, J., Nikkanen, J., Iosifidis, A. & Gabbouj, M. (2021). INTEL-TAU: A Color Constancy Dataset. IEEE Access, 9, 39560-39567. Artikel 9371681. https://doi.org/10.1109/ACCESS.2021.3064382

Feng, H., Gomes, C., Thule, C., Lausdahl, K., Iosifidis, A. & Larsen, P. G. (2021). Introduction to Digital Twin Engineering. I C. R. Martin, M. J. Blas & A. I. Psijas (red.), 2021 Annual Modeling and Simulation Conference (ANNSIM) (s. 1-12). IEEE. https://doi.org/10.23919/ANNSIM52504.2021.9552135

Nielsen, A. H., Iosifidis, A. & Karstoft, H. (2021). IrradianceNet: Spatiotemporal Deep Learning Model for Satellite-Derived Solar Irradiance Nowcasting. Solar Energy, 228, 659-669. https://doi.org/10.1016/j.solener.2021.09.073

Laakom, F., Chumachenko, K., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2021). Learning to ignore: rethinking attention in CNNs. I 32rd British Machine Vision Conference https://arxiv.org/pdf/2111.05684.pdf

Bajovic, D., Bakhtiarnia, A., Bravos, G., Brutti, A., Burkhardt, F., Cauchi, D., Chazapis, A., Cianco, C., Dall'Asen, N., Delic, V., Dimou, C., Djokic, D., Escobar-Molero, A., Esterle, L., Eyben, F., Farella, E., Festi, T., Geromitsos, A., Giakoumakis, G. ... Zammit, J. (2021). MARVEL: Multimodal Extreme Scale Data Analytics for Smart Cities Environments. I 2021 International Balkan Conference on Communications and Networking, BalkanCom 2021 (s. 143-147). IEEE. https://doi.org/10.1109/BalkanCom53780.2021.9593258

Feng, H., Gomes, C., Iosifidis, A. & Larsen, P. G. (2021). Model-based monitoring and state estimation for digital twins: The Kalman filter. I C. R. Martin, M. J. Blas & A. I. Psijas (red.), Annual Modeling and Simulation Conference (ANNSIM 2021) (s. 1-2)

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

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

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. Artikel 9070152. https://doi.org/10.1109/TNNLS.2020.2984831

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

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Revideret 10.08.2023

Alexandros Iosifidis