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    2019

    1. N.Tsapanos, A.Tefas, N.Nikolaidis and I.Pitas, "Neurons With Paraboloid Decision Boundaries for Improved Neural Network Classification Performance", IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 30, issue 1, pp. 284-294, 2019.
    2. V. Mygdalis, A.Tefas and I.Pitas, "Exploiting Multiplex Data Relationships in Support Vector Machines", Pattern Recognition, Elsevier, vol. 85, pp. 70-77, 2019.
    3. I. Mademlis, N.Nikolaidis, A.Tefas, I.Pitas, T. Wagner and A. Messina, "Autonomous Unmanned Aerial Vehicles Filming in Dynamic Unstructured Outdoor Environments", IEEE Signal Processing Magazine, vol. 36, issue 1, pp. 147-153, 2019.
    4. N. Passalis and A.Tefas, "Deep Reinforcement Learning for Controlling Frontal Person Close-up Shooting", Neurocomputing, Elsevier, vol. 335, pp. 37-47, 2019.
    5. M. Tzelepi and A.Tefas, "Graph Embedded Convolutional Neural Networks in Human Crowd Detection for Drone Flight Safety", IEEE Transactions on Emerging Topics in Computational Intelligence, accepted for publication, 2019.
    6. P. Nousi, A. Tsantekidis, N. Passalis, A.Tefas, J. Kanniainen, M. Gabbouj and A.Iosifidis, "Machine Learning for Forecasting Mid Price Movement Using Limit Order Book Data", IEEE Access, 2019.
    7. G. Mourgias-Alexandris, A. Tsakyridis, N. Passalis, A.Tefas, K. Vyrsokinos and N. Pleros, "A Sigmoid Optical Neuron for Photonic Neural Network Applications", Optics Express, 2019.
    8. I. Mademlis, N.Nikolaidis, A.Tefas, I.Pitas, T. Wagner and A. Messina, "Autonomous UAV Cinematography: A Tutorial and a Formalized Shot-Type Taxonomy", ACM Computing Surveys, vol. 52, issue 5, pp. 105:1-105:33, 2019.

    2018

    1. D. Triantafyllidou, P. Nousi and A.Tefas, "Fast Deep Convolutional Face Detection in the Wild Exploiting Hard Sample Mining", Big Data Research, Elsevier, vol. 11, pp. 65-76, 2018.
    2. V. Mygdalis, A.Iosifidis, A.Tefas and I.Pitas, "Semi-Supervised Subclass Support Vector Data Description for Image and Video Classification", Neurocomputing, Elsevier, vol. 291, pp. 237-241, 2018 (Code).
    3. I. Mademlis, A.Tefas and I.Pitas, "A Salient Dictionary Learning Framework for Activity Video Summarization via Key-frame Extraction", Information Sciences, vol. 432, pp. 319-331, 2018.
    4. M. Tzelepi and A.Tefas, "Deep Convolutional Image Retrieval: A General Framework", Signal Processing: Image Communication, Elsevier, vol. 63, pp. 30-43, 2018.
    5. P. Nousi and A.Tefas, "Self-Supervised Autoencoders for Clustering and Classification", Evolving Systems Journal, Springer, pp. 1-14, 2018.
    6. V. Lioutas, N. Passalis and A.Tefas, "Explicit Ensemble Attention Learning for Improving Visual Question Answering", Pattern Recognition Letters, vol. 111, pp. 51-57, 2018.
    7. N. Passalis and A.Tefas, "Learning Bag-of-Embedded-Words Representations for Textual Information Retrieval", Pattern Recognition, vol. 81, pp. 254-267, 2018.
    8. N. Passalis and A.Tefas, "PySEF: A Python Library for Similarity-based Dimensionality Reduction", Knowledge-Based Systems, vol. 152, pp. 186-187, 2018.
    9. E. Kakaletsis, O.Zoidi, I. Tsingalis, A.Tefas, N.Nikolaidis and I.Pitas, "Fast Constrained Person Identity Label Propagation in Stereo Videos Using a Pruned Similarity Matrix", Signal Processing: Image Communication, Elsevier, 2018.
    10. M. Tzelepi and A.Tefas, "Deep Convolutional Learning for Content Based Image Retrieval", Neurocomputing, vol. 275, pp. 2467-2478, 2018.
    11. N. Kondylidis, M. Tzelepi and A.Tefas, "Exploiting tf-idf in Deep Convolutional Neural Networks for Content Based Image Retrieval", Multimedia Tools and Applications, pp. 1-20, 2018.
    12. N. Passalis and A.Tefas, "Unsupervised Knowledge Transfer Using Similarity Embeddings", IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 30, issue 3, pp. 946-950, 2018.
    13. N. Passalis and A.Tefas, "Long Term Temporal Averaging for Stochastic Optimization of Deep Neural Networks", Neural Computing and Applications, 2018 (accepted).
    14. E. Daskalakis, M. Tzelepi and A.Tefas, "Learning Deep Spatiotemporal Features for Video Captioning", Pattern Recognition Letters, 2018.
    15. N. Passalis and A.Tefas, "Training Lightweight Deep Convolutional Neural Networks Using Bag-of-Features Pooling", IEEE Transactions on Neural Networks and Learning Systems, accepted for publication, 2018.
    16. 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, 2018.
    17. D. Spathis, N. Passalis and A.Tefas, "Interactive Dimensionality Reduction Using Similarity Projections", Knowledge-Based Systems, 2018.

    2017

    1. P. Chriskos, O.Zoidi, A.Tefas and I.Pitas, "De-Identifying Facial Images Using Singular Value Decomposition and Projections", Multimedia Tools and Applications, Springer, vol. 76, issue 3, pp. 3435-3468, 2017.
    2. N. Passalis and A.Tefas, "Dimensionality Reduction using Similarity-induced Embeddings", IEEE Transactions on Neural Networks and Learning Systems, 2017.
    3. P. Nousi and A.Tefas, "Deep Learning Algorithms for Discriminant Autoencoding", Neurocomputing, Elsevier, vol. 266, pp. 325-335, 2017.
    4. V. Gogousis and A.Tefas, "Caricature Generation Utilizing the Notion of Anti-Face", Multimedia Tools and Applications, Springer (accepted), 2017.
    5. N. Passalis and A.Tefas, "Learning Neural Bag-of-Features for Large-Scale Image Retrieval", IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017.

    2016

    1. N. Passalis and A.Tefas, "Entropy Optimized Feature-Based Bag-of-Words Representation for Information Retrieval", IEEE Transactions on Knowledge and Data Engineering, Vol. 28, no. 7, pp. 1664-1677, 2016.
    2. N. Passalis and A.Tefas, "Information Clustering Using Manifold-Based Optimization of the Bag-of-Features Representation", IEEE Transactions on Cybernetics, 2016.
    3. N. Passalis and A.Tefas, "Neural Bag-of-Features Learning", Pattern Recognition, 2016.
    4. O.Zoidi, A.Tefas, N.Nikolaidis and I.Pitas, "Positive and negative label propagation", IEEE Transactions on Circuits and Systems for Video Technology, 2016.
    5. A.Iosifidis, A.Tefas and I.Pitas, "Approximate kernel extreme learning machine for large scale data classification", Neurocomputing, 2016.
    6. I.Kapsouras, A.Tefas, N.Nikolaidis, G. Peeters, L. Benaroya and I.Pitas, "Multimodal speaker clustering in full length movies", Multimedia Tools and Applications, pp. 1-20, 2016.
    7. A.Iosifidis, V. Mygdalis, A.Tefas and I.Pitas, "One-Class Classification based on Extreme Learning and Geometric Class Information", Neural Processing Letters, pp. 1-16, 2016 (Code).
    8. A.Iosifidis, A.Tefas and I.Pitas, "Graph Embedded Extreme Learning Machine", IEEE Transactions on Cybernetics, vol. 46, no. 1, pp. 311-324, 2016.
    9. J.Blat, A.Evans, H.Kim, E.Imre, L.Polok, V.Ila, N.Nikolaidis, P.Zemcik, A.Tefas, P.Smrz, A.Hilton and I.Pitas, "Big Data Analysis for Media Production", Proceedings of the IEEE, 2016.
    10. F. Patrona, A.Iosifidis, A.Tefas, N.Nikolaidis and I.Pitas, "Visual Voice Activity Detection in the Wild", IEEE Transactions on Multimedia, vol. 18, no. 6, pp. 967 - 977, 2016.
    11. I. Mademlis, A.Iosifidis, A.Tefas, N.Nikolaidis and I.Pitas, "Exploiting stereoscopic disparity for augmenting human activity recognition performance", Multimedia Tools and Applications, vol. 75, no. 19, pp. 11641-11660, 2016.
    12. I. Mademlis, A.Tefas, N.Nikolaidis and I.Pitas, "Multimodal Stereoscopic Movie Summarization Conforming to Narrative Characteristics", IEEE Transactions on Image Processing, vol. 25, no. 12, pp. 5828-5840, 2016.
    13. 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, 2016 (Code).

    2015

    1. D.Bouzas, N.Arvanitopoulos and A.Tefas, "Graph Embedded Nonparametric Mutual Information For Supervised Dimensionality Reduction", IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 5, pp. 951 - 963, 2015.
    2. A.Iosifidis, A.Tefas and I.Pitas, "Class-specific Reference Discriminant Analysis with application in Human Behaviour Analysis", IEEE Transactions on Human Machine Systems, vol. 45, pp. 315-326, 2015 (Code).
    3. A.Iosifidis, A.Tefas and I.Pitas, "On the Kernel Extreme Learning Machine Classifier", Pattern Recognition Letters, vol. 54, pp. 11-17, 2015.
    4. A.Iosifidis, A.Tefas and I.Pitas, "DropELM: Fast Neural Network Regularization with Dropout and DropConnect", Neurocomputing, vol. 162, pp. 57-66, 2015 (Code).
    5. A.Iosifidis, A.Tefas and I.Pitas, "Distance-based Human Action Recognition using optimized class representations", Neurocomputing, vol. 161, pp. 47-55, 2015 (Code).
    6. A.Iosifidis, A.Tefas and I.Pitas, "Sparse Extreme Learning Machine classifier exploiting Intrinsic Graphs", Pattern Recognition Letters, vol. 65, pp. 192-196, 2015.
    7. N.Tsapanos, A.Tefas, N.Nikolaidis and I.Pitas, "A Distributed Framework for Trimmed Kernel k-means Clustering", Pattern Recognition, vol. 48, pp. 2685–2698, 2015.
    8. N.Vretos, A.Tefas and I.Pitas, "A Novel Dimensionality Reduction Technique based on Kernel Optimization Through Graph Embedding", Signal, Image and Video Processing, 2015.
    9. A.Iosifidis, A.Tefas and I.Pitas, "Human Action Recognition based on Multi-view Regularized Extreme Learning Machine", International Journal on Artificial Intelligence Tools, vol. 45, no. 5, 2015.
    10. 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.
    11. A.Maronidis, A.Tefas and I.Pitas, "Subclass Graph Embedding and a Marginal Fisher Analysis paradigm", Pattern Recognition, vol. 48, pp. 4024-4035, 2015.
    12. G.Orphanidis, A.Tefas, N.Nikolaidis and I.Pitas, "Facial image clustering in stereoscopic videos using double spectral analysis", Signal Processing: Image Communication, vol. 33, pp. 86-105, 2015.
    13. C.Chrysouli and A.Tefas, "Spectral clustering and semi-supervised learning using evolving similarity graphs", Applied Soft Computing, vol. 34, pp. 625-637, 2015.

    2014

    1. O.Zoidi, A.Tefas, N.Nikolaidis and I.Pitas, "Person identity label propagation in stereo videos", IEEE Transactions on Multimedia, vol. 16, issue 5, pp. 1358-1368, 2014.
    2. 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.
    3. S.Nikitidis, A.Tefas and I.Pitas, "Maximum Margin Projection Subspace Learning for Visual Data Analysis", IEEE Transactions on Image Processing, vol. 23, no. 10, pp. 4413 - 4425, 2014.
    4. S.Nikitidis, A.Tefas and I.Pitas, "Projected Gradients for Subclass Discriminant Nonnegative Subspace Learning", IEEE Transactions on Cybernetics, vol. 44, no. 12, pp. 2806 - 2819, 2014.
    5. 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 (Code).
    6. A.Iosifidis, A.Tefas and I.Pitas, "Kernel Reference Discriminant Analysis", Pattern Recognition Letters, vol. 49, pp. 85-91, 2014 (Code).
    7. O.Zoidi, N.Nikolaidis, A.Tefas and I.Pitas, "Stereo Object Tracking with Fusion of Texture, Color and Disparity Information", Signal Processing: Image Communication, vol. 29, Issue 5, pp. 573-589, 2014.
    8. K. Papachristou, A.Tefas and I.Pitas, "Symmetric Subspace Learning for Image Analysis", IEEE Transactions on Image Processing, vol. 23, no. 12, pp. 5683-5697, 2014.

    2013

    1. O.Zoidi, A.Tefas and I.Pitas, "Visual Object Tracking based on Local Steering Kernels and Color Histograms", in IEEE Transactions on Circuits and Systems for Video Technology, vol. 23, no. 5, pp. 870-882, may, 2013.
    2. A.Iosifidis, A.Tefas and I.Pitas, "Learning sparse representations for view-independent human action recognition based on fuzzy distances", Neurocomputing, vol. 121C, pp. 334-353, 2013 (Code).
    3. 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.
    4. N.Vretos, A.Tefas and I.Pitas, "Using robust dispersion estimation in support vector machines", Pattern Recognition, Volume 46, Issue 12, 2013.
    5. 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.
    6. 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, 1968-1979, 2013 (Code).
    7. 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, November, 2013.
    8. O.Zoidi, A.Tefas and I.Pitas, "Multiplicative Update Rules for Concurrent Nonnegative Matrix Factorization and Maximum Margin Classification", in IEEE Transactions on Neural Networks and Learning Systems, Vol 24, Issue 3,pp 422 - 434, March, 2013.
    9. 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. 1-7, 2013.

    2012

    1. A.Iosifidis, A.Tefas, N.Nikolaidis and I.Pitas, "Multi-view human movement recognition based on Fuzzy distances and Linear Discriminant Analysis", Computer Vision and Image Understanding, vol. 116, pp. 347-360, March, 2012.
    2. A.Iosifidis, A.Tefas and I.Pitas, "Activity based Person Identification using Fuzzy Representation and Discriminant Learning", IEEE Transactions in Information Forensics and Security, vol.7, no.2, pp.530-542, April, 2012.
    3. 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, March, 2012.
    4. S.Nikitidis, A.Tefas, N.Nikolaidis and I.Pitas, "Subclass Discriminant Non negative Matrix Factorization for Facial Image Analysis", Pattern Recognition, vol. 45, issue 12, pp. 4080-4091, December, 2012.
    5. N.Tsapanos, A.Tefas, N.Nikolaidis and I.Pitas, "Shape matching using a binary search tree structure of weak classifiers", Pattern Recognition, vol. 45, no. 6, pp. 2363-2376, 2012.

    2011

    1. A.Maronidis, D.Bolis, A.Tefas and I.Pitas, "Improving subspace learning for facial expression recognition using person dependent and geometrically enriched training sets", Neural Networks, Volume 24, Issue 8,, 814-823, October, 2011.

    2010

    1. M.Kyperountas, A.Tefas and I.Pitas, "Salient feature and reliable classifier selection for facial expression classification", Pattern Recognition, New York, USA, 972-986, 2010.
    2. N.Tsapanos, A.Tefas and I.Pitas, "Online Shape Learning using Binary Search Trees", Image and Vision Computing, vol. 28, issue 7, pp. 1146 - 1154, July, 2010.

    2009

    1. G.Goudelis, A.Tefas and I.Pitas, "Automated Facial Pose Extraction From Video Sequences Based on Mutual Information", IEEE Transactions on Circuits and Systems for Video Technology, vol. 18, no. 3, pp. 418 - 424, March, 2009.

    2008

    1. N.Gkalelis, A.Tefas and I.Pitas, "Combining fuzzy vector quantization with linear discriminant analysis for continuous human movement recognition", IEEE Transactions on Circuits and Systems for Video Technology, vol. 18, no. 11, pp. 1511-1521, November, 2008.
    2. G.Goudelis, A.Tefas and I.Pitas, "Emerging Biometric Modalities: a Survey", Journal on Multimodal User Interfaces, Springer, vol. 2, no. 3-4, pp. 217 - 235, 2008.
    3. M.Kyperountas, A.Tefas and I.Pitas, "Dynamic Training using Multistage Clustering for Face Recognition", Pattern Recognition, Elsevier, vol. 41, no. 3, pp. 894-905, 2008.

    2007

    1. G.Goudelis, S.Zafeiriou, A.Tefas and I.Pitas, "Class-Specific Kernel Discriminant Analysis for Face Verification", IEEE Transactions on Information Forensics and Security, vol. 2, no. 3, part 2, pp. 570-587, September, 2007 (Special issue on Human Detection and Recognition).
    2. M.Kyperountas, A.Tefas and I.Pitas, "Weighted piecewise LDA for solving the small sample size problem in face verification", IEEE Transactions on Neural Networks, vol. 18, no. 2, pp. 506-519, 2007.
    3. S.Zafeiriou, A.Tefas and I.Pitas, "The discriminant elastic graph matching algorithm applied to frontal face verification", Pattern Recognition, vol. 40, no. 10, pp. 2798-2810, October, 2007.
    4. S.Zafeiriou, A.Tefas and I.Pitas, "Learning Discriminant Person-Specific Facial Models Using Expandable Graphs", IEEE Transactions on Information Forensics and Security, vol. 2, no. 1, pp. 55-68, March, 2007.
    5. S.Zafeiriou, A.Tefas and I.Pitas, "Minimum Class Variance Support Vector Machines", IEEE Transactions on Image Processing, vol. 16, no. 10, pp. 2551-2564, October, 2007.

    2006

    1. S.Zafeiriou, A.Tefas, I.Buciu and I.Pitas, "Exploiting Discriminant Information in Non-negative Matrix Factorization with application to Frontal Face Verification", IEEE Transactions on Neural Networks, vol. 17, no. 3, pp. 683-695, May, 2006.

    2005

    1. S.Zafeiriou, A.Tefas and I.Pitas, "Blind Robust Watermarking Schemes for Copyright Protection of 3D Mesh Objects", IEEE Transactions on Visualization and Computer Graphics, vol. 11, no. 5, pp 596-607, September-October, 2005.

    2003

    1. A.Tefas, A.Nikolaidis, N.Nikolaidis, V.Solachidis, S.Tsekeridou and I.Pitas, "Markov chaotic sequences for correlation based watermarking schemes", Chaos, Solitons and Fractals, vol. 17, pp. 567-573, 2003.
    2. A.Tefas, A.Nikolaidis, N.Nikolaidis, V.Solachidis, S.Tsekeridou and I.Pitas, "Performance Analysis of Correlation-based Watermarking Schemes employing Markov Chaotic Sequences", IEEE Transactions on Signal Processing, vol. 51, no. 7, pp. 1979 - 1994, July, 2003.

    2002

    1. A.Tefas, C.Kotropoulos and I.Pitas, "Face verification using elastic graph matching based on morphological signal decomposition", Signal Processing, vol. 82, no. 6, June, 2002.

    2001

    1. F.Bartollini, A.Tefas, M.Barni and I.Pitas, "Image Authentication Techniques for Surveillance Applications", Proceedings of the IEEE, vol. 89, no. 10, September, 2001.
    2. A.Tefas, C.Kotropoulos and I.Pitas, "Using Support vector machines to enhance the performance of elastic graph matching for frontal face authentication", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, no. 7, July, 2001.
    3. S.Tsekeridou, V.Solachidis, N.Nikolaidis, A.Nikolaidis, A.Tefas and I.Pitas, "Statistical Analysis of a Watermarking System based on Bernoulli Chaotic Sequences, Signal Processing", Elsevier Special Issue on Information Theoretic Issues in Digital Watermarking, vol. 81, no. 6, pp. 1273-1293, 2001.

    2000

    1. C.Kotropoulos, A.Tefas and I.Pitas, "Frontal face authentication using discriminating grids with morphological feature vectors", IEEE Transactions on Multimedia, vol. 2, no. 1, March, 2000.
    2. C.Kotropoulos, A.Tefas and I.Pitas, "Frontal face authentication using morphological elastic graph matching", IEEE Transactions on Image Processing, vol. 9, no. 4, April, 2000.
    3. C.Kotropoulos, A.Tefas and I.Pitas, "Morphological elastic graph matching applied to frontal face authentication under well-controlled and real conditions", Pattern Recognition, vol. 33, no. 12, October, 2000.

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