Publications

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Laakom, F., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2021). On Feature Diversity in Energy-based models. Afhandling præsenteret på International Conference on Learning Representations Workshop on Energy-Based Models, , Vienna. https://openreview.net/pdf?id=ks3Q08yy66r

Heidari, N. & Iosifidis, A. (2021). On the spatial attention in spatio-temporal graph convolutional networks for skeleton-based human action recognition. I IJCNN 2021 - International Joint Conference on Neural Networks, Proceedings IEEE. https://doi.org/10.1109/IJCNN52387.2021.9534440

Kharghanian, R., Peiravi, A., Moradi, F. & Iosifidis, A. (2021). Pain detection using batch normalized discriminant restricted Boltzmann machine layers. Journal of Visual Communication and Image Representation, 76, Artikel 103062. https://doi.org/10.1016/j.jvcir.2021.103062

Heidari, N. & Iosifidis, A. (2021). Progressive Graph Convolutional Networks for Semi-Supervised Node Classification. IEEE Access, 9, 81957-81968. https://doi.org/10.1109/ACCESS.2021.3085905

Heidari, N. & Iosifidis, A. (2021). Progressive Spatio-Temporal Graph Convolutional Network for Skeleton-Based Human Action Recognition. I ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (Bind 2021-June, s. 3220-3224). IEEE. https://doi.org/10.1109/ICASSP39728.2021.9413860

Chumachenko, K., Laakom, F., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2021). Rethinking compactness in deep neural networks. Afhandling præsenteret på International Conference on Machine Learning Workshop on Overparameterization. https://drive.google.com/file/d/1pu5xJMPvKuGFeVCcylEvLz00uLK3UN9I/view

Laakom, F., Raitoharju, J., Nikkanen, J., Iosifidis, A. & Gabbouj, M. (2021). Robust channel-wise illumination estimation. I 32rd British Machine Vision Conference https://arxiv.org/pdf/2111.05681.pdf

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

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

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

Soltanian, M., Malik, J., Raitoharju, J., Iosifidis, A., Kiranyaz, S. & Gabbouj, M. (2021). Speech Command Recognition in Computationally Constrained Environments with a Quadratic Self-Organized Operational Layer. I 2021 International Joint Conference on Neural Networks (IJCNN) IEEE. https://doi.org/10.1109/IJCNN52387.2021.9534232

Chumachenko, K., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2021). Speed-up and Multi-view Extensions to Subclass Discriminant Analysis. Pattern Recognition, 111, Artikel 107660. https://doi.org/10.1016/j.patcog.2020.107660

Hedegaard Morsing, L., Sheikh-Omar, O. A. & Iosifidis, A. (2021). Supervised Domain Adaptation: A Graph Embedding Perspective and a Rectified Experimental Protocol. IEEE Transactions on Image Processing, 30, 8619-8631. https://doi.org/10.1109/TIP.2021.3118978

Hedegaard Morsing, L., Sheikh-Omar, O. A. & Iosifidis, A. (2021). Supervised Domain Adaptation using Graph Embedding. Afhandling præsenteret på 25th International Conference on Pattern Recognition, Milan, Italien. https://arxiv.org/abs/2003.04063

Heidari, N. & Iosifidis, A. (2021). Temporal Attention-Augmented Graph Convolutional Network for Efficient Skeleton-Based Human Action Recognition. I Proceedings of ICPR 2020 - 25th International Conference on Pattern Recognition (s. 7907-7914). Artikel 9412091 IEEE. https://doi.org/10.1109/ICPR48806.2021.9412091

Leporowski, B. & Iosifidis, A. (2021). Visualising deep network time-series representations. Neural Computing and Applications, 33(23), 16489-16498. https://doi.org/10.1007/s00521-021-06244-8

Laakom, F., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2021). Within-layer Diversity Reduces Generalization Gap. Afhandling præsenteret på International Conference on Machine Learning Workshop on Information Theoretic Methods for Rigorous, Responsible, and Reliable Machine Learning, 2021. https://arxiv.org/pdf/2106.06012.pdf

Oleksiienko, I. & Iosifidis, A. (2022). 3D object detection and tracking. I A. Iosifidis & A. Tefa (red.), Deep Learning for Robot Perception and Cognition (s. 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, Artikel 105017. https://doi.org/10.1016/j.cageo.2021.105017

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. I 2022 IEEE International Smart Cities Conference (ISC2) IEEE. https://doi.org/10.1109/ISC255366.2022.9921939

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

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

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

Hedegaard Morsing, L. & Iosifidis, A. (2022). Continual 3D Convolutional Neural Networks for Real-time Processing of Videos. I S. Avidan, G. Brostow, M. Cissé, G. M. Farinella & T. Hassner (red.), Computer Vision – ECCV 2022 - 17th European Conference, 2022, Proceedings (s. 369-385). Springer. https://doi.org/10.1007/978-3-031-19772-7_22

Hedegaard Morsing, L., Bakhtiarnia, A. & Iosifidis, A. (2022). Continual Transformers: Redundancy-Free Attention for Online Inference. The Eleventh International Conference on Learning Representations. https://arxiv.org/abs/2201.06268

Dong, Z., Li, N., Iosifidis, A. & Zhang, Q. (2022). Design and Prototyping Distributed CNN Inference Acceleration in Edge Computing. ArXiv. https://doi.org/10.48550/arXiv.2211.13778

Leporowski, B. T., Tola, D., Hansen, C. & Iosifidis, A. (2022). Detecting Faults during Automatic Screwdriving: A Dataset and Use Case of Anomaly Detection for Automatic Screwdriving. 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. 224-232). Springer. https://doi.org/10.1007/978-3-030-90700-6_25

Li, N., Iosifidis, A. & Zhang, Q. (2022). Distributed Deep Learning Inference Acceleration using Seamless Collaboration in Edge Computing. I ICC 2022 - IEEE International Conference on Communications (s. 3667-3672). IEEE. https://doi.org/10.1109/ICC45855.2022.9839083

Wan, S., Chen, C. & Iosifidis, A. (2022). Editorial to special issue on cross-media learning for visual question answering. Image and Vision Computing, 118, Artikel 104355. https://doi.org/10.1016/j.imavis.2021.104355

Chumachenko, K., Iosifidis, A. & Gabbouj, M. (2022). Feedforward Neural Networks Initialization based on Discriminant Learning. Neural Networks, 146, 220-229. https://doi.org/10.1016/j.neunet.2021.11.020

Nielsen, A. H., Iosifidis, A. & Karstoft, H. (2022). Forecasting large-scale circulation regimes using deformable convolutional neural networks and global spatiotemporal climate data. Scientific Reports, 12(1), Artikel 8395. https://doi.org/10.1038/s41598-022-12167-8

Heidari, N., Hedegaard Morsing, L. & Iosifidis, A. (2022). Graph convolutional networks. I A. Iosifidis & A. Tefas (red.), Deep Learning for Robot Perception and Cognition (s. 71-99). Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00009-9

Laakom, F., Raitoharju, J., Passalis, N., Iosifidis, A. & Gabbouj, M. (2022). Graph Embedding with Data Uncertainty. IEEE Access, 10, 24232-24239. https://doi.org/10.1109/ACCESS.2022.3155233

Li, N., Iosifidis, A. & Zhang, Q. (2022). Graph Reinforcement Learning-based CNN Inference Offloading in Dynamic Edge Computing. I 2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings (s. 982-987). IEEE. https://doi.org/10.1109/GLOBECOM48099.2022.10001067

Morsing, L. H., Heidari, N. & Iosifidis, A. (2022). Human Activity Recognition. I A. Iosifidis & A. Tefas (red.), Deep Learning for Robot Perception and Cognition (s. 341-370). Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00019-1

Iosifidis, A. & Tefas, A. (2022). Introduction. I A. Iosifidis & A. Tefas (red.), Deep Learning for Robot Perception and Cognition Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00006-3

Shabani, M., Tran, D. T., Magris, M., Kanniainen, J. & Iosifidis, A. (2022). Multi-head Temporal Attention-Augmented Bilinear Network for Financial time series prediction. I 30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings (s. 1487-1491). IEEE. https://doi.org/10.23919/EUSIPCO55093.2022.9909957

Chumachenko, K., Gabbouj, M. & Iosifidis, A. (2022). Object detection and tracking. I A. Iosifidis & A. Tefas (red.), Deep Learning for Robot Perception and Cognition (s. 243-278). Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00016-6

Kakavandi, F., de Reus, R., Gomes, C., Heidari, N., Iosifidis, A. & Larsen, P. G. (2022). Product Quality Control in Assembly Machine under Data Restricted Settings. I 2022 IEEE 20th International Conference on Industrial Informatics, INDIN 2022 (s. 735-741). IEEE. https://doi.org/10.1109/INDIN51773.2022.9976173

Tran, D. T., Gabbouj, M. & Iosifidis, A. (2022). Progressive and compressive learning. I A. Iosifidis & A. Tefas (red.), Deep Learning for Robot Perception and Cognition (s. 187-220). Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00014-2

Li, N., Iosifidis, A. & Zhang, Q. (2022). Receptive Field-based Segmentation for Distributed CNN Inference Acceleration in Collaborative Edge Computing. I ICC 2022 - IEEE International Conference on Communications (s. 4281-4286). IEEE. https://doi.org/10.1109/ICC45855.2022.9838547

Tran, D. T., Gabbouj, M. & Iosifidis, A. (2022). Remote Multilinear Compressive Learning with Adaptive Compression. IEEE Internet of Things Journal, 9(9), 6905-6913. https://doi.org/10.1109/jiot.2021.3114743

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

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

Hedegaard Morsing, L., Alok, A., Jose, J. & Iosifidis, A. (2022). Structured Pruning Adapters. https://doi.org/10.48550/arXiv.2211.10155

Oleksiienko, I., Tran, D. T. & Iosifidis, A. (2022). Variational Neural Networks implementation in Pytorch and JAX[Formula presented]. Software Impacts, 14, Artikel 100431. https://doi.org/10.1016/j.simpa.2022.100431

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), Artikel 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. I M. Zorzi, M. Tao & W. Saad (red.), ICC 2023 - IEEE International Conference on Communications (s. 967-972). IEEE. https://doi.org/10.1109/ICC45041.2023.10279110

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

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Revideret 10.08.2023

Alexandros Iosifidis