This page was last updated in 2022. A more complete list of publications can be found in Google Scholar and DBLP.
Preprints under review in journals
N. Zehtabiyan-Rezaie, A. Iosifidis and M. Abkar, "Physics-guided machine learning for wind-farm power prediction: Toward interpretability and generalizability", arXiv:2212.04188
M. Magris and A. Iosifidis, "Bayesian Learning for Neural Networks: an algorithmic survey", arXiv:2211.11865
M. Refiei, J. Raitoharju and A. Iosifidis, "Computer Vision on X-ray Data in Industrial Production and Security Applications: A survey", arXiv:2211.05565
A. Bakhtiarnia, Q. Zhang and A. Iosifidis, "Efficient High-Resolution Deep Learning: A Survey", arXiv:2207.1350
M. Shabani, M. Magris, G. Tzagkarakis, J. Kanniainen and A. Iosifidis, "Predicting the State of Synchronization of Financial Series using Cross Recurrence Plots", arXiv:2210.14605
M. Refiei, D. T. Tran and A. Iosifidis, "Recognition of Defective Minear Wool using Pruned ResNet Models", arXiv:2211.00466
M. Shabani, D. T. Tran, J. Kanniainen and A. Iosifidis, "Augmented Bilinear Network for Incremental Multi-Stock Time-Series Classification", arXiv:2207.11577
I. Oleksiienko, P. Nousi, N. Passalis, A. Tefas and A. Iosifidis, “VPIT: Real-time Embedded Single Object 3D Tracking Using Voxel Pseudo Images”, arXiv:2206.02619
A. Cavaga, N. Li, A. Iosifidis and Q. Zhang, "Semantic Communication Enabling Robust Edge Intelligence for Time-Critical IoT Applications", arXiv:2211.13787
A. Mannisto, M. Seker, A. Iosifidis and J. Raitoharju, "Automatic Image Content Extraction: Operationalizing Machine Learning in Humanistic Photographic Studies of Large Visual Archives", arXiv:2204.02149
L. Hedegaard, N. Heidari and A. Iosifidis, “Online Skeleton-based Action Recognition with Continual Spatio-Temporal Graph Convolutional Networks”, arXiv:2203.11009
D.T. Tran, J. Kanniainen and A. Iosifidis, “How informative is the order book beyond the best levels? Machine Learning perspective”, arXiv:2203.07922
F. Laakom, J. Raitoharju, N. Passalis, A. Iosifidis and M. Gabbouj, "Non-Linear Spectral Dimensionality Reduction Under Uncertainty", arXiv:2202.04678
R. Jensen and A. Iosifidis, "Fighting Money Laundering with Statistics and Machine Learning: An Introduction and Review", arXiv:2201.04207
D.T. Tran, M. Gabbouj and A. Iosifidis, “Multilinear Compressive Learning with Prior Knowledge”, arXiv:2002.07203
J. Raitoharju and A. Iosifidis, “Null Space Analysis for Class-Specific Discriminant Learning”, arXiv:1908.04562
Editorials
S. Wan, C. Chen and A. Iosifidis, “Cross-Media Learning for Visual Question Answering”, Image and Vision Computing, 104355, 2022
A. Iosifidis and A. Tefas, “Deep Learning for Visual Content Analysis”, Signal Processing: Image Communication, vol 83, 115806, 2020
A. Iosifidis, A. Tefas, I. Pitas and M. Gabbouj, “Big Media Data Analysis”, Signal Processing: Image Communication, vol. 59, pp. 105-108, 2017
Journal papers
M. Seker, A. Mannisto, A. Iosifidis and J. Raitoharju, “Automatic Social Distance Estimation from Images: Performance Evaluation, Test Benchmark, and Algorithm”, Machine Learning with Applications, accepted October 2022
I. Oleksiienko, D. T. Tran and A. Iosifidis, “Variational Neural Networks implementation in Pytorch and JAX”, Software Impacts, accepted October 2022
R. I. T. Jensen and A. Iosifidis, “Qualifying and Raising Anti-Money Laundering Alarms with Deep Learning”, Expert Systems with Applications, accepted October 2022
C. M. Legaard, T. Schranz, G. Schweiger, J. Drgona, B. Falay, C. Gomes, A. Iosifidis, M. Abkar and P. G. Larsen, “Constructing Neural Network-Based Models for Simulating Dynamical Systems”, ACM Computing Surveys, accepted October 2022
F. Sohrab, A. Iosifidis, M. Gabbouj and J. Raitoharju, "Graph-Embedded Subspace Support Vector Data Description", Pattern Recognition, accepted August 2022
N. Li, A. Iosifidis and Q. Zhang, “Collaborative Edge Computing for Distributed CNN Inference Acceleration using Receptive field-based Segmentation”, Computer Networks, accepted July 2022
A. Bakhtiarnia, Q. Zhang and A. Iosifidis, “Single-Layer Vision Transformer for More Accurate Early Exits with Less Overhead”, Neural Networks, accepted June 2022
M. R. Mann, A. Iosifidis, J. U. Jepsen, J. M. Welker, M. J. J. E. Loonen and T. T. Hoye, “Automatic flower detection and phenology monitoring using time-lapse cameras and deep learning”, Remote Sensing in Ecology and Conservation, accepted May 2022
N. Zehtabiyan-Rezaie, A. Iosifidis and M. Abkar, “Data-driven fluid mechanics of wind farms: A review”, Journal of Renewable and Sustainable Energy, accepted April 2022
D.T. Tran, N. Passalis, A. Tefas, M. Gabbouj and A. Iosifidis, "Attention-based Neural Bag-of-Features Learning for Sequence Data", IEEE Access, accepted April 2022
A.H. Nielsen, A. Iosifidis and H. Karstoft, “Forecasting large-scale circulation regimes using deformable convolutional neural networks and global spatiotemporal climate data”, Scientific Reports, vol. 12, article number 8395, 2022
F. Laakom, J. Raitoharju, N. Passalis, A. Iosifidis and M. Gabbouj, "Graph Embedding with Data Uncertainty", IEEE Access, accepted Febr. 2022
K. Chumachenko, A. Iosifidis and M. Gabbouj, “Feedforward Neural Networks Initialization based on Discriminant Learning”, Neural Networks, vol. 146, pp. 220-229, 2022
L.H. Morsing, O.A. Sheikh-Omar and A. Iosifidis, “Supervised Domain Adaptation: A Graph Embedding Perspective and a new experimental protocol”, IEEE Transactions on Image Processing, vol. 30, pp. 8619-8631, 2021
D.T. Tran, M. Gabbouj and A. Iosifidis, “Remote Multilinear Compressive Learning with Adaptive Compression”, IEEE Internet of Things journal, accepted September 2021
A.H. Nielsen, A. Iosifidis and H. Karstoft, “IrradianceNet: Spatiotemporal Deep Learning Model for Satellite-Derived Solar Irradiance Nowcasting”, Solar Energy, vol. 228, pp. 659-669, 2021
B. Leporowski and A. Iosifidis, "Visualising Deep Network's Time-Series Representations", Neural Computing and Applications, vol. 33, pp. 1689-1698, 2021
N. Heidari and A. Iosifidis, "Progressive Graph Convolutional Networks for Semi-Supervised Node Classification", IEEE Access, vol. 9, pp. 81957-81968, 2021
L. Xu, J. Raitoharju, A. Iosifidis and M. Gabbouj, "Saliency-based Weighted Multi-label Linear Discriminant Analysis", IEEE Transactions on Cybernetics, accepted March 2021
S. Kiranyaz, J. Malik, H.B. Abdallah, T. Ince, A. Iosifidis and M. Gabbouj, "Self-Organized Operational Neural Networks with Generative Neurons", Neural Networks, vol. 140, pp. 294-308, 2021
A.H. Nielsen, A. Iosifidis and H. Karstoft, "CloudCast: A Satelite-based Dataset and Baseline for Forecasting Clouds", IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 3485-3494, 2021
R. Kharghanian, A. Peiravi, F. Moradi and A. Iosifidis, "Pain Detection using Batch Normalized Discriminant Restricted Botzmann Machine Layers", Journal of Visual Communication and Image Representation, vol. 76:103062, 2021
F. Laakom, J. Raitoharju, A. Iosifidis, J. Nikkanen and M. Gabbouj, “INTEL-TAU: A Color Constancy Dataset”, IEEE Access, vol. 9, pp. 39560-39567, 2021
N. Passalis, J. Kanniainen, M. Gabbouj, A. Iosifidis and A. Tefas, "Forecasting Financial Time Series using Robust Deep Adaptive Input Normalization", Journal of Signal Processing Systems, DOI: 10.1007/s11265-020-01624-0, 2021
S. Kiranyaz, J. Malik, H.B. Abdallah, T. Ince, A. Iosifidis and M. Gabbouj, “Exploiting Heterogeneity in Operational Neural Networks by Synaptic Plasticity”, Neural Computing and Applications, DOI: 10.1007/s00521-020-05543-w, 2021
T.T. Høye, J. Ärje, K. Bjerge, O.L.P. Hansen, A. Iosifidis, F. Leese, H.M.R. Mann, K. Meissner, C. Melvad and J. Raitoharju, “Deep learning and computer vision will transform entomology”, Proceedings of the National Academy of Sciences of the United States of America, vol. 118, no. 2, ID: 2020-02545RRR, 2021
J. Malik, S. Kiranyaz, R.I. Al-Raoush, O. Monga, P. Garnier, S. Foufou, A. Bouras, A. Iosifidis, M. Gabbouj, and P.C. Baveye, “3D Quantum Cuts for Automatic Segmentation of Porous Media in Tomography Images”, Computers and Geosciences, accepted November 2021
A. Iosifidis, "Class Mean Vector Component and Discriminant Analysis", Pattern Recognition Letters, vol. 140, no. 2, pp. 207-213, 2020
A. Iosifidis, "Probabilistic Class-Specific Discriminant Analysis", IEEE Access, vol. 8, pp. 183847-183855, 2020
K. Chumachenko, J. Raitoharju, A. Iosifidis and M. Gabbouj, "Speed-up and multi-view extensions to Subclass Discriminant Analysis", Pattern Recognition, vol. 111, 107660, 2021
C. Gautam, A. Riwari, P.K. Mishra, S. Suresh, A. Iosifidis and M. Tanveer, “Graph-Embedded Multi-layer Kernel Ridge Regression for One-class Classification”, Cognitive Computation, vol. 13, pp. 552-569, 2021
F. Sohrab, J. Raitoharju, A. Iosifidis and M. Gabbouj, "Multimodal Subspace Support Vector Data Description", Pattern Recognition, vol. 110, 107648, 2021
N. Passalis, A. Iosifidis, M. Gabbouj and A. Tefas, “Hypersphere-based Weight Imprinting for Few-shot Learning on Embedded Devices”, IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 2, pp. 925-930, 2021
D.T. Tran, M. Yamac, A. Degerli, M. Gabbouj and A. Iosifidis, “Multilinear Compressive Learning”, IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 4, pp. 1512-1524, 2021
G. Cao, A. Iosifidis, M. Gabbouj, V. Raghavan and R. Gottumukkala, "Deep Multi-view Learning to Rank", IEEE Transactions on Knowledge and Data Engineering, vol. 33, no. 4, pp. 1426-1438, 2021
K. Chumachenko, A. Mannisto, A. Iosifidis and J. Raitoharju, "Machine Learning based Analysis of Finnish World War II Photographers", IEEE Access, vol. 8, pp. 144184 – 144196, 2020
F. Sohrab, J. Raitoharju, A. Iosifidis and M. Gabbouj, “Ellipsoidal Subspace Support Vector Data Description”, IEEE Access, vol. 8, pp. 122013-122025, 2020
F. Laakom, N. Passalis, J. Raitoharju, J. Nikkanen, A. Tefas, A. Iosifidis and M. Gabbouj, “Bag of Color Features for Color Constancy”, IEEE Transactions on Image Processing, vol. 29, pp. 7722 – 7734, 2020
J. Arje, J. Raitoharju, A. Iosifidis, V. Tirronen, K. Meissner, M. Gabbouj, S. Kiranyaz and S. Karkkainen, “Human experts vs. machines in taxa recognition”, Signal Processing: Image Communication, vol. 87:115917, pp. 1-10, 2020
N. Passalis, A. Tefas, J. Kanniainen, M. Gabbouj and A. Iosifidis, “Temporal Logistic Neural Bag-of-Features for Financial Time series Forecasting leveraging Limit Order Book Data”, Pattern Recognition Letters, vol.136, 183-189, 2020
A. Ntakaris, J. Kanniainen, M. Gabbouj and A. Iosifidis, “Mid-price Prediction Based on Machine Learning Methods with Technical and Quantitative Indicators”, PLoS ONE, e0234107, DOI: 10.1371/journal.pone.0234107, 2020
J. Arje, C. Melvad, M.R. Jeppesen, S.A. Madsen, J. Raitoharju, M.S. Rasmussen, A. Iosifidis, V. Tirronen, M. Gabbouj, K. Meissner and T.T. Hoye, “Automatic image-based identification and biomass estimation if invertebrates”, Methods in Ecology and Evolution, vol. 1, no. 8, pp. 922-931, 2020
A. Tsantekidis, N. Passalis, A. Tefas, J. Kanniainen, M. Gabbouj and A. Iosifidis, “Using Deep Learning for price prediction by exploiting stationary limit order book features”, Applied Soft Computing, accepted May 2020
M Krestenitis, N. Passalis, A. Iosifidis, M. Gabbouj and A. Tefas, “Recurrent Bag-of-Features for Visual Information Analysis”, Pattern Recognition, accepted March 2020
N. Passalis, A. Tefas, J. Kanniainen, M. Gabbouj and A. Iosifidis, “Deep Adaptive Input Normalization for Time Series Forecasting”, IEEE Transactions on Neural Networks and Learning Systems, vol. 3, no. 9, pp. 3760-3765, 2020
S. Kiranyaz, T. Ince, A. Iosifidis and M. Gabbouj, “Operational Neural Networks”, Neural Computing and Applications, vol. 32, pp. 6645–6668, 2020
N. Passalis, A. Iosifidis, M. Gabbouj and A. Tefas, “Variance-preserving Deep Metric Learning for Content-based Image Retrieval”, Pattern Recognition Letters, vol. 131, pp. 8-14, 2020
D.T. Tran, S. Kiarnyaz, M. Gabbouj and A. Iosifidis, "Heterogeneous Multilayer Generalized Operational Perceptron", IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 3, pp. 710-724 , 2020
O.L.P. Hansen, J.C. Svenning, K. Olsen, S. Dupont, B.H. Garner, A. Iosifidis, B.W. Price, T.T. Høye, “Species-level image classification with convolutional neural network enable insect identification from habitus images”, Ecology and Evolution, DOI: 10.1002/ece3.5921, 2019
D.T. Tran, S. Kiranyaz, M. Gabbouj and A. Iosifidis, “Progressive Operational Perceptrons with Memory”, Neurocomputing, vol. 379, pp. 172-181, 2019
A. Ntakaris, G. Mirone, J. Kanniainen, M. Gabbouj and A. Iosifidis, "Feature Engineering for Mid-Price Prediction with Deep Learning", IEEE Access, vol. 7, pp. 82390 – 82412, 2019
M. Makinen, J. Kanniainen, M. Gabbouj and A. Iosifidis, “Forecasting of Jump Arrivals in Stock Prices: New Attention-based Network Architecture using Limit Order Book Data”, Quantitative Finance, vol. 19, no. 12, pp. 2033-2050, 2019
D.T. Tran, S. Kiranyaz, M. Gabbouj and A. Iosifidis, “PyGOP: A Python Library for Generalized Operational Perceptron”, Knowledge-Based Systems, Volume 182, 104801, 15 October 2019
P. Nousi, A. Tsantekidis, N. Passalis, A. Ntakaris, J. Kanniainen, A. Tefas, M. Gabbouj and A. Iosifidis, "Machine Learning for Forecasting Mid Price Movement using Limit Order Book Data", IEEE Access, vol. 7, pp. 64722-64736, 2019
N. Passalis, A. Tefas, J. Kanniainen, M. Gabbouj and A. Iosifidis, “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, (Early Access) DOI: 10.1109/TETCI.2018.2872598, 2019
D.T. Tran, A. Iosifidis, J. Kanniainen and M. Gabbouj, “Temporal Attention augmented Bilinear Network for Financial Time-Series Data Analysis”, IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 5, pp. 1407-1418, 2019
A. Ntakaris, M. Magris, J. Kanniainen, M. Gabbouj and A. Iosifidis, “Benchmark Dataset for Mid-Price Prediction of Limit Order Book data”, Journal of Forecasting, DOI:10.1002/for.2543, 2018
J. Raitoharju, E. Riabchenko, I. Ahmad, A. Iosifidis, M. Gabbouj, S. Kiranyaz, V. Torronen, J. Arje, S. Karkkainen and K. Meissner, “Benchmark Database for Find-Grained Image Classification of Benthic Macroinvertebrates”, Image and Vision Computing, vol. 78, pp. 73-83, 2018
D.T. Tran, A. Iosifidis and M. Gabbouj, “Improving Efficiency in Convolutional Neural Network with Multilinear Filters”, accepted in Neural Networks journal, vol. 105, pp. 328-339, 2018
G. Cao, A. Iosifidis, K. Chen and M. Gabbouj, “Generalized Multi-view Embedding for Visual Recognition and Cross-modal Retrieval”, IEEE Transactions on Cybernetics, vol. 48, no. 9, pp. 2542-2555, 2018
C. Aytekin, A. Iosifidis and M. Gabbouj, “Probabilistic Saliency Estimation”, Pattern Recognition, vol. 74, pp. 359-372, 2018
G. Cao, A. Iosifidis and M. Gabbouj, “Neural Class-Specific Regression for Face Verification”, IET Biometrics, vol. 7, no. 1, pp. 63-70, 2018
V. Mygdalis, A. Iosifidis, A. Tefas and I. Pitas, “Semi-Supervised Subclass Support Vector Data Description for Image and Video Classification”, Neurocomputing, vol. 278, pp. 51-61, 2018 (Corrigendum vol. 291, pp. 237-241, 2018)
D.T. Tran, M. Gabbouj and A. Iosifidis, “Multilinear Class-Specific Discriminant Analysis”, Pattern Recognition Letters, vol. 100, pp. 131-136, 2017
G. Cao, A. Iosifidis and M. Gabbouj, “Multi-view Nonparametric Discriminant Analysis for Image Retrieval and Recognition”, IEEE Signal Processing Letters, vol. 24, no. 10, pp. 1537-1541, 2017
A. Iosifidis and M. Gabbouj, “Class-Specific Kernel Discriminant Analysis revisited: further analysis and extensions”, IEEE Transactions on Cybernetics, vol. 47, no. 12, pp. 4485-4496, 2017
M.A. Waris, A. Iosifidis and M. Gabbouj, “CNN-based Edge Filtering for Object Proposals”, Neurocomputing, vol. 266, pp. 631-640, 2017
S. Kaveh, A. Iosifidis and M. Gabbouj, “On the comparison of random and Hebbian weights for the training of single-hidden layer feedforward neural networks”, Expert Systems with Application, vol. 83, pp. 177-186, 2017
C. Aytekin, A. Iosifidis and M. Gabbouj, “'Learning Graph Affinities for Spectral Graph-based Salient Object Detection”, Pattern Recognition, vol. 64, pp. 159-167, 2017
S. Kiranyaz, T. Ince, A. Iosifidis and M. Gabbouj, “Progressive Operational Perceptrons”, Neurocomputing, vol. 224, pp. 142-154, 2017
J. Arje, S. Karkkainen, K. Meissner, A. Iosifidis, T. Ince, M. Gabbouj and S. Kiranyaz, “The effect of automated taxa identification errors on biological indices”, Expert Systems with Applications, vol. 72, pp. 108-120, 2017
A. Iosifidis, A. Tefas and I. Pitas, “Approximate Kernel Extreme Learning Machine for Large-Scale Data Classification”, Neurocomputing, vol. 219, pp. 210-220, 2017
A. Iosifidis, V. Mygdalis, A. Tefas and I. Pitas, “One-Class Classification based on Extreme Learning and Geometric Class Information”, Neural Processing Letters, vol. 45, pp. 577-592, 2017
A. Iosifidis and M. Gabbouj, “Scaling up Class-Specific Kernel Discriminant Analysis for large-scale Face Verification”, IEEE Transactions on Information Forensics and Security, vol. 11, no. 11, pp. 2453-2465, 2016
V. Mygdalis, A. Iosifidis, A. Tefas and I. Pitas, “Graph Embedded One-Class Classifiers for media data classification”, Pattern Recognition, vol. 60, pp. 585-595, 2017
A. Iosifidis and M. Gabbouj, “Nyström-based Approximate Kernel Subspace Learning”, Pattern Recognition, vol. 57, pp. 190-197, 2016
F. Patrona, A. Iosifidis, A. Tefas and I. Pitas, “Visual Voice Activity Detection in the Wild”, IEEE Transactions on Multimedia, vol. 18, no. 6, pp. 967-977, 2016
A. Iosifidis and M. Gabbouj, “Multi-class Support Vector Machine Classifiers using Intrinsic and Penalty Graphs”, Pattern Recognition, vol. 55, pp. 231-246, 2016
A. Iosifidis, A. Tefas and I. Pitas, “Graph Embedded Extreme Learning Machine”, IEEE Transactions on Cybernetics, vol. 46, no. 1, pp. 311-324, 2016
C. Aytekin, S. Kiranyaz, A. Iosifidis and M. Gabbouj, “Recent Advances in Salient Object Detection – Towards Object Recognition in Big Media Data”, Futura – Big Data, vol. 35, no. 2, pp. 80-92, 2016
A. Iosifidis and M. Gabbouj, “On the kernel Extreme Learning Machine speedup”, Pattern Recognition Letters, vol. 68, pp. 205-210, 2015
A. Iosifidis, A. Tefas and I. Pitas, “Class-specific Reference Discriminant Analysis with application in Human Behavior Analysis”, IEEE Transactions on Human-Machine Systems, vol. 45, no. 3, 315-326, 2015
A. Iosifidis, “Extreme Learning Machine based Supervised Subspace Learning”, Neurocomputing, vol. 167, pp. 158-164, 2015
A. Iosifidis, A. Tefas and I. Pitas, “Sparse Extreme Learning Machine classifier exploiting Intrinsic Graphs”, Pattern Recognition Letters, vol. 65, pp. 192-196, 2015
I. Mademlis, A. Iosifidis, A. Tefas, N. Nikolaidis and I. Pitas, “Exploiting Stereoscopic Disparity for Augmenting Human Activity Recognition Performance”, Multimedia Tools & Applications, vol. 75, pp. 11641-11660, 2016
A. Iosifidis, A. Tefas and I. Pitas, “DropELM: Fast Neural Network Regularization with Dropout and DropConnect”, Neurocomputing, vol. 162, pp. 57-66, 2015
A. Iosifidis, A. Tefas and I. Pitas, “Distance-based Human Action Recognition using optimized class representations”, Neurocomputing, vol. 161, pp. 47-55, 2015
A. Iosifidis, A. Tefas and I. Pitas, “On the Kernel Extreme Learning Machine Classifier”, Pattern Recognition Letters, vol. 54, pp. 11-17, 2015
A. Iosifidis, E. Marami, A. Tefas, I. Pitas and K. Lyroudia, “The MOBISERV-AIIA Eating and Drinking multi-view database for vision-based assisted living”, Journal of Information Hiding and Multimedia Signal Processing, vol. 6, no. 2, pp. 254-273, 2015
A. Iosifidis, A. Tefas and I. Pitas, “Human Action Recognition based on Multi-view Regularized Extreme Learning Machine”, International Journal on Artificial Intelligence Tools, 2015
A. Iosifidis, A. Tefas and I. Pitas, “Kernel Reference Discriminant Analysis”, Pattern Recognition Letters, vol. 49, pp. 85-91, 2014
A. Iosifidis, A. Tefas and I. Pitas, “Discriminant Bag of Words based Representation for Human Action Recognition”, Pattern Recognition Letters, vol. 49, pp. 185-192, 2014
A. Iosifidis, A. Tefas and I. Pitas, “Regularized Extreme Learning Machine for Multi-view Semi-supervised Action Recognition”, Neurocomputing, vol. 145, pp. 250-262, 2014
A. Iosifidis, A. Tefas and I. Pitas, “Multidimensional Sequence Classification based on Fuzzy Distances and Discriminant Analysis”, IEEE Transactions on Knowledge and Data Engineering, vol. 93, no. 6, pp. 1445-1457, 2013
A. Iosifidis, A. Tefas and I. Pitas, “Minimum Class Variance Extreme Learning Machine for Human Action Recognition”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 23, no. 11, pp. 1968-1979, 2013
A. Iosifidis, A. Tefas and I. Pitas, “Dynamic action recognition based on Dynemes and Extreme Learning Machine”, Pattern Recognition Letters, vol. 34, pp. 1890-1898, 2013
A. Iosifidis, A. Tefas and I. Pitas, “Learning sparse representations for view-independent human action recognition based on fuzzy distances”, Neurocomputing, vol. 121, pp. 334-353, 2013
A. Iosifidis, A. Tefas and I. Pitas, “On the optimal class representation in Linear Discriminant Analysis”, IEEE Transactions on Neural Networks and Learning Systems, vol. 24, no. 9, pp. 1491-1497, 2013
A. Iosifidis, A. Tefas and I. Pitas, "Multi-view Action Recognition Based on Action Volumes, Fuzzy Distances and Cluster Discriminant Analysis", Signal Processing, vol. 93, pp. 1445-1457, 2013
A. Iosifidis, A. Tefas and I. Pitas, "View-invariant action recognition based on Artificial Neural Networks", IEEE Transactions on Neural Networks and Learning Systems, vol. 23, no. 3, pp. 412-424, 2012
A. Iosifidis, A. Tefas, N. Nikolaidis and I. Pitas, "Multi-view Human Movement Recognition based on Fuzzy Distances and Linear Discriminant Analysis", Computer Vision & Image Understanding, vol. 116, pp. 347-360, 2012
A. Iosifidis, A. Tefas and I. Pitas, "Activity based Person Identification using Fuzzy Representation and Discriminant Learning", IEEE Transactions on Information Forensics and Security, vol. 7, no. 2, pp. 530-542, 2012
A. Iosifidis, S.G. Mouroutsos and A. Gasteratos, “A hybrid static/active video surveillance system”, International Journal of Optomechatronics, vol. 5, no. 1, pp. 80-95, 2011