Nikolaos Papamarkos

Scopus Publications

Interpretable Vision Transformers in Monocular Depth Estimation via SVDA
Vasileios Arampatzakis, George Pavlidis, Nikolaos Mitianoudis, Nikos Papamarkos
Mathematics, 2026
Monocular depth estimation is a central problem in computer vision with applications in robotics, augmented reality, and autonomous driving, yet the self-attention mechanisms used by modern Transformer architectures remain opaque. In this work, we integrate SVD-Inspired Attention (SVDA) into the Dense Prediction Transformer (DPT), introducing a spectrally structured attention formulation for dense prediction that decouples directional alignment from spectral modulation through a learnable diagonal matrix embedded in normalized query–key interactions. Experiments on KITTI and NYU-v2 show that SVDA preserves competitive predictive performance while enabling intrinsic interpretability: on KITTI, AbsRel improves from 0.058 to 0.056 and δ1 from 0.976 to 0.979, while on NYU-v2, AbsRel improves from 0.133 to 0.124 and δ1 from 0.865 to 0.872. This is achieved with only 0.01% additional parameters, at the cost of a measurable runtime overhead associated with the added normalization and spectral modulation. More importantly, SVDA enables six spectral indicators that quantify entropy, rank, sparsity, alignment, selectivity, and robustness, revealing consistent cross-dataset and depth-wise patterns in how attention organizes during training. These properties make the model easier to inspect and better suited to applications where transparency and reliability are important, such as robotics and autonomous navigation.
On Segment-Aware Monocular Depth Estimation Using Vision Transformers
Vasileios Arampatzakis, George Pavlidis, Nikolaos Mitianoudis, Nikos Papamarkos
Information Switzerland, 2026
Monocular Depth Estimation (MDE) infers per-pixel scene geometry from a single RGB image. Despite recent progress, global MDE models often blur depth discontinuities at object boundaries and fail to capture object-level structure. Segment-aware depth estimation addresses this limitation by exploiting semantic segmentation to decompose depth prediction into simpler, class-specific subproblems. In this work, we study semantic-aware MDE in a multi-branch design where each semantic class is handled by a lightweight Vision Transformer (ViT) branch that predicts dense depth for its class while suppressing interference from other regions. We further examine fusion strategies that merge the branch outputs into a single prediction: (i) a learnable cross-attention fusion module that predicts depth from the stack of per-class proposals and masks, and (ii) a parameter-free stitched summation that sums mask-gated outputs. The proposed architecture is simple, scalable, end-to-end trainable, and compatible with arbitrary transformer backbones. Experiments on Virtual KITTI 2, where ground-truth depth and semantic labels are available, show that segment-aware modeling produces sharper depth boundaries and improves standard error metrics compared to a single-branch baseline (AbsRel 0.243→0.152; RMSE 11.952→9.101). Finally, we find that the parameter-free summation matches, and in most cases improves upon, the accuracy of learned fusion while adding no computational overhead.
Interpretable Vision Transformers in Image Classification via SVDA
Vasileios Arampatzakis, George Pavlidis, Nikolaos Mitianoudis, Nikos Papamarkos
IEEE Access, 2026
Vision Transformers (ViTs) have achieved state-of-the-art performance in image classification, yet their attention mechanisms often remain opaque and exhibit dense, non-structured behaviors. In this work, we adapt our previously proposed SVD-Inspired Attention (SVDA) mechanism to the ViT architecture, introducing a geometrically grounded formulation that enhances interpretability, sparsity, and spectral structure. We apply the use of interpretability indicators—originally proposed with SVDA—to monitor attention dynamics during training and assess structural properties of the learned representations. Experimental evaluations on four widely used benchmarks—CIFAR-10, FashionMNIST, CIFAR-100, and ImageNet-100—together with an additional pretrained fine-tuning study in a standard ViT setting show that SVDA preserves competitive classification behavior in our experimental settings while providing descriptive diagnostics of attention structure. In the pretrained setting, we integrate the exact SVDA operator into the late transformer blocks of a standard pretrained ViT and fine-tune on ImageNet-100, providing additional evidence that the proposed mechanism remains viable beyond compact from-scratch training. While the current framework offers descriptive insights rather than prescriptive guidance, our results establish SVDA as a comprehensive and informative tool for analyzing and developing structured attention models in computer vision. This work lays the foundation for future advances in explainable AI, spectral diagnostics, and attention-based model design.
Geometry Meets Attention: Interpretable Transformers via SVD Inspiration
Vasileios Arampatzakis, George Pavlidis, Nikolaos Mitianoudis, Nikos Papamarkos
IEEE Access, 2025
Self-attention is a cornerstone of modern deep learning, yet its dense dot-product formulation offers limited interpretability and lacks explicit structural constraints. We propose <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SVD-inspired Attention</i> (SVDA), a novel self-attention mechanism that introduces normalized query/key projections and a learnable diagonal spectral modulation, drawing direct motivation from the structure of Singular Value Decomposition (SVD). This formulation separates directional alignment from spectral emphasis, offering a geometrically grounded and interpretable variant of attention. We formalize SVDA within a standard multi-head Transformer architecture and introduce a suite of structure-aware indicators—such as spectral entropy, effective rank, and selectivity—that quantify interpretability and sparsity in attention dynamics. Our analysis highlights SVDA’s capacity for structured, energy-aware attention without compromising architectural compatibility or expressiveness. This work provides a theoretical foundation and diagnostic framework for structured attention models aimed at interpretability, compression, and semantic transparency.
Towards Explainability in Monocular Depth Estimation
Vasileios Arampatzakis, George Pavlidis, Kyriakos Pantoglou, Nikolaos Mitianoudis, Nikos Papamarkos
Communications in Computer and Information Science, 2025
Monocular Depth Estimation: A Thorough Review
Vasileios Arampatzakis, George Pavlidis, Nikolaos Mitianoudis, Nikos Papamarkos
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024
Estimation of depth in two-dimensional images is among the challenging topics in Computer Vision. This is a well-studied but also an ill-posed problem, which has long been the focus of intense research. This paper is an in-depth review of the topic, presenting two aspects, one that considers the mechanisms of human depth perception, and another that includes the various Deep Learning approaches. The methods are presented in a compact and structured way that outlines the topic and categorizes the approaches according to the line of research followed in the recent decade. Although there has been significant advancement in the topic, it was without any connection with human depth perception and the potential benefits from this sector.
A Dilated MultiRes Visual Attention U-Net for historical document image binarization
Nikolaos Detsikas, Nikolaos Mitianoudis, Nikolaos Papamarkos
Signal Processing Image Communication, 2024
Towards memristive crossbar-based neuromorphic HW accelerators for signal processing
I. Vourkas, A. Abusleme, N. Vasileiadis, G. Ch. Sirakoulis, N. Papamarkos
2017 6th International Conference on Modern Circuits and Systems Technologies Mocast 2017, 2017
Research progress in neuromorphic hardware, capable of biological perception and cognitive information processing, is leading the way towards a revolution in computing technology. Current research efforts have focused mainly on resistive switching devices, the electronic analog of synapses in artificial neural networks (ANNs), and the crossbar nanoarchitecture, for its huge connectivity and maximum integration density. In this context, this work presents the design and simulation of a memristive crossbar-based ANN for text recognition tasks, implementing a novel computing algorithm. In such case study, important issues during the application mapping process are identified and properly addressed at device and circuit level. The computing capabilities of the proposed system are highlighted through SPICE-level circuit simulations, which show excellent agreement with theoretical simulation results.
A system for restoration and structural retrieval of documents
Maria Ntonti, Nikos Papamarkos
Proceedings of the IASTED International Conference on Modelling Identification and Control, 2017
This paper describes a new technique for document retrieval using a web camera in an office environment. The architecture of the aforementioned method consists of three main stages: segmentation, restoration and retrieval. Firstly, the document image is taken with a web camera and the segmentation process is applied to locate the four corners of the document and isolate it. Then we proceed to document restoration by applying filtering, skew and curvature correction as well as removal of any redundant object that does not belong to the document. In the third and final stage, a feature vector is extracted and is compared with the documents of the database.
Applying conformal geometry for creating a 3D model spatial-consistent texture map
George Ioannakis, Christodoulos Chamzas, Anestis Koutsoudis, Nikolaos Papamarkos, Ioannis Pratikakis, Fotis Arnaoutoglou, Nikolaos Mitianoudis, Thomas Sgouros
2016 Digital Media Industry and Academic Forum Dmiaf 2016 Proceedings, 2016
The aim of this research is to achieve spatial consistency of the UV map. We present an approach to produce a fully spatially consistent UV mapping based on the planar parameterisation of the mesh. We apply our method on a 3D digital replica of an ancient Greek Lekythos vessel. We parameterise the mesh of a 3D model onto a unit square 2D plane using computational conformal geometry techniques. The proposed method is genus independent, due to an iterative 3D mesh cutting procedure. Having now the texture of a 3D model depicted on a spatially continuous two dimensional structure enables us to efficiently apply a vast range of image processing based techniques and algorithms.
A new sharpening technique for medical images using wavelets and image fusion
P. Zafeiridis, , N. Papamarkos, S. Goumas, I. Seimenis, , , and
Journal of Engineering Science and Technology Review, 2016
Document image binarization using local features and Gaussian mixture modeling
Nikolaos Mitianoudis, Nikolaos Papamarkos
Image and Vision Computing, 2015
Local Co-occurrence and Contrast Mapping for Document Image Binarization
Nikolaos Mitianoudis, Nikolaos Papamarkos
Proceedings of International Conference on Frontiers in Handwriting Recognition Icfhr, 2014
Microcalcification oriented content-based mammogram retrieval for breast cancer diagnosis
Lazaros Tsochatzidis, Konstantinos Zagoris, Michalis Savelonas, Nikos Papamarkos, Ioannis Pratikakis, Nikolaos Arikidis, Lena Costaridou
Ist 2014 2014 IEEE International Conference on Imaging Systems and Techniques Proceedings, 2014
A Dynamic Gesture and Posture Recognition System
Kyriakos Sgouropoulos, Ekaterini Stergiopoulou, Nikos Papamarkos
Journal of Intelligent and Robotic Systems Theory and Applications, 2014
A novel image sharpening technique based on 2D-DWT and image fusion
Fusion 2014 17th International Conference on Information Fusion, 2014
Distinction between handwritten and machine-printed text based on the bag of visual words model
Konstantinos Zagoris, Ioannis Pratikakis, Apostolos Antonacopoulos, Basilis Gatos, Nikos Papamarkos
Pattern Recognition, 2014
Multi-spectral document image binarization using image fusion and background subtraction techniques
Nikolaos Mitianoudis, Nikolaos Papamarkos
2014 IEEE International Conference on Image Processing Icip 2014, 2014
Real time hand detection in a complex background
Ekaterini Stergiopoulou, Kyriakos Sgouropoulos, Nikos Nikolaou, Nikos Papamarkos, Nikos Mitianoudis
Engineering Applications of Artificial Intelligence, 2014
Conversion of color documents to grayscale
Iliana Papamarkou, Nikos Papamarkos
2013 21st Mediterranean Conference on Control and Automation MED 2013 Conference Proceedings, 2013
Guidance, navigation, and control of an unmanned hovercraft
Kilsoo Kim, Young-Ki Lee, Sehwan Oh, David Moroniti, Dimitri Mavris, George J. Vachtsevanos, Nikos Papamarkos, George Georgoulas
2013 21st Mediterranean Conference on Control and Automation MED 2013 Conference Proceedings, 2013
Automatic summarization and annotation of videos with lack of metadata information
Dim P. Papadopoulos, Vicky S. Kalogeiton, Savvas A. Chatzichristofis, Nikos Papamarkos
Expert Systems with Applications, 2013
Handwritten and Machine Printed text separation in document images using the bag of Visual Words Paradigm
Konstantinos Zagoris, Ioannis Pratikakis, Apostolos Antonacopoulos, Basilis Gatos, Nikos Papamarkos
Proceedings International Workshop on Frontiers in Handwriting Recognition Iwfhr, 2012
Video summarization using a self-growing and self-organized neural gas network
Dim P. Papadopoulos, Savvas A. Chatzichristofis, Nikos Papamarkos
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2011
Text localization using standard deviation analysis of structure elements and support vector machines
Konstantinos Zagoris, Savvas A Chatzichristofis, Nikos Papamarkos
Eurasip Journal on Advances in Signal Processing, 2011
Robust document binarization with OFF center-surround cells
V. Vonikakis, I. Andreadis, N. Papamarkos
Pattern Analysis and Applications, 2011
Image retrieval systems based on compact shape descriptor and relevance feedback information
Konstantinos Zagoris, Kavallieratou Ergina, Nikos Papamarkos
Journal of Visual Communication and Image Representation, 2011
Text extraction using component analysis and neuro-fuzzy classification on complex backgrounds
Michael Makridis, Nikolaos E. Mitrakis, Nikolaos Nikolaou, Nikolaos Papamarkos
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2011
Automatic image annotation and retrieval using the joint composite descriptor
Konstantinos Zagoris, Savvas A. Chatzichristofis, Nikos Papamarkos, Yiannis S. Boutalis
Proceedings 14th Panhellenic Conference on Informatics PCI 2010, 2010
A Document Image Retrieval System
Konstantinos Zagoris, Kavallieratou Ergina, Nikos Papamarkos
Engineering Applications of Artificial Intelligence, 2010
A new technique for solving puzzles
Michael Makridis, Nikos Papamarkos
IEEE Transactions on Systems Man and Cybernetics Part B Cybernetics, 2010
An adaptive layer-based local binarization technique for degraded documents
MICHAEL MAKRIDIS, N. PAPAMARKOS
International Journal of Pattern Recognition and Artificial Intelligence, 2010
Accurate image retrieval based on compact composite descriptors and relevance feedback information
SAVVAS A. CHATZICHRISTOFIS, KONSTANTINOS ZAGORIS, YIANNIS S. BOUTALIS, NIKOS PAPAMARKOS
International Journal of Pattern Recognition and Artificial Intelligence, 2010
Text extraction using document structure features and support vector machines
K. Zagoris, N. Papamarkos
Proceedings of the 11th IASTED International Conference on Computer Graphics and Imaging Cgim 2010, 2010
An adaptive technique for global and local skew correction in color documents
Michael Makridis, Nikos Nikolaou, Nikos Papamarkos
Expert Systems with Applications, 2010
Segmentation of historical machine-printed documents using Adaptive Run Length Smoothing and skeleton segmentation paths
Nikos Nikolaou, Michael Makridis, Basilis Gatos, Nikolaos Stamatopoulos, Nikos Papamarkos
Image and Vision Computing, 2010
Development and evaluation of text localization techniques based on structural texture features and neural classifiers
Christos Emmanouilidis, Costas Batsalas, Nikos Papamarkos
Proceedings of the International Conference on Document Analysis and Recognition ICDAR, 2009
Estimation of appropriate parameter values for document binarization techniques
E. Badekas, N. Papamarkos
International Journal of Robotics and Automation, 2009
Hand gesture recognition using a neural network shape fitting technique
E. Stergiopoulou, N. Papamarkos
Engineering Applications of Artificial Intelligence, 2009
img(Anaktisi): A web content based image retrieval system
Konstantinos Zagoris, Savvas A. Chatzichristofis, Nikos Papamarkos, Yiannis S. Boutalis
2009 2nd International Workshop on Similarity Search and Applications Sisap 2009, 2009
Color quantization based on PCA and kohonen SOFM
D. Mavridis, N. Papamarkos
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
Color reduction for complex document images
Nikos Nikolaou, Nikos Papamarkos
International Journal of Imaging Systems and Technology, 2009
Color quantization using principal components for initialization of Kohonen SOFM
Dimitris Mavridis, Nikos Papamarkos
Proceedings International Conference on Image Processing Icip, 2009
Estimation of proper parameter values for document binarization
Proceedings of the 10th IASTED International Conference on Computer Graphics and Imaging Cgim 2008, 2008
An evaluation technique for binarization algorithms
Journal of Universal Computer Science, 2008
DEVELOPING document image retrieval system
Mccsis 08 Iadis Multi Conference on Computer Science and Information Systems Proceedings of Computer Graphics and Visualization 2008 and Gaming 2008 Design for Engaging Experience Soc Interaction, 2008
Exact image reconstruction from a limited number of projections
A.L. Kesidis, N. Papamarkos
Journal of Visual Communication and Image Representation, 2008
Local skew correction in documents
P. SARAGIOTIS, N. PAPAMARKOS
International Journal of Pattern Recognition and Artificial Intelligence, 2008
An evaluation survey of binarization algorithms on historical documents
Pavlos Stathis, Ergina Kavallieratou, Nikos Papamarkos
Proceedings International Conference on Pattern Recognition, 2008
Document binarisation using Kohonen SOM
E. Badekas, N. Papamarkos
Iet Image Processing, 2007
Optimal combination of document binarization techniques using a self-organizing map neural network
E. Badekas, N. Papamarkos
Engineering Applications of Artificial Intelligence, 2007
Skew correction in documents with several differently skewed text areasskew correction in documents with several differently skewed text areas
Visapp 2007 2nd International Conference on Computer Vision Theory and Applications Proceedings, 2007
Color Segmentation of Complex Document Images
N. Nikolaou, N. Papamarkos
Communications in Computer and Information Science, 2007
Color reduction using the combination of the Kohonen self-organized feature map and the Gustafson-Kessel fuzzy algorithm
Konstantinos Zagoris, Nikos Papamarkos, Ioannis Koustoudis
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2007
A new technique for global and local skew correction in binary documents
Michael Makridis, Nikos Nikolaou, Nikos Papamarkos
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2007
Adaptive document binarization : A human vision approach
Visapp 2007 2nd International Conference on Computer Vision Theory and Applications Proceedings, 2007
A new technique for hand gesture recognition
E. Stergiopoulou, N. Papamarkos
Proceedings International Conference on Image Processing Icip, 2006
A new technique for solving a jigsaw puzzle
M. Makridis, N. Papamarkos
Proceedings International Conference on Image Processing Icip, 2006
Web document image retrieval system based on word spotting
K. Zagoris, N. Papamarkos, C. Chamzas
Proceedings International Conference on Image Processing Icip, 2006
Text binarization in color documents
Efthimios Badekas, Nikos Nikolaou, Nikos Papamarkos
International Journal of Imaging Systems and Technology, 2006
Color reduction and estimation of the number of dominant colors by using a self-growing and self-organized neural gas
Antonios Atsalakis, Nikos Papamarkos
Engineering Applications of Artificial Intelligence, 2006
Exact grayscale image reconstruction from projections
ANASTASIOS L. KESIDIS, NIKOS PAPAMARKOS
International Journal of Pattern Recognition and Artificial Intelligence, 2006
Color segmentation of complex document images
Visapp 2006 Proceedings of the 1st International Conference on Computer Vision Theory and Applications, 2006
Text localization in color documents
Visapp 2006 Proceedings of the 1st International Conference on Computer Vision Theory and Applications, 2006
Automatic edge detection by combining Kohonen SOM and the Canny operator
P. Sampaziotis, N. Papamarkos
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2005
Color reduction by using a new self-growing and self-organized neural network
Institute of Mathematics and Its Applications Vision Video and Graphics 2005 Vvg 2005, 2005
Grayscale image reconstruction from projections with linear noise response
A.L. Kesidis, N. Papamarkos
IEEE Workshop on Signal Processing Systems Sips Design and Implementation, 2005
Automatic evaluation of document binarization results
E. Badekas, N. Papamarkos
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2005
Image dominant colors estimation and color reduction via a new self-growing and self-organized neural gas
A. Atsalakis, N. Papamarkos, I. Andreadis
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2005
Hand gesture recognition via a new self-organized neural network
E. Stergiopoulou, N. Papamarkos, A. Atsalakis
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2005
An innovative algorithm for solving jigsaw puzzles using geometrical and color features
M. Makridis, N. Papamarkos, C. Chamzas
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2005
A multi-segment image coding and transmission scheme
G. Pavlidis, A. Tsompanopoulos, N. Papamarkos, C. Chamzas
Signal Processing, 2005
Colour quantisation technique based on image decomposition and its embedded system implementation
A. Atsalakis, N. Papamarkos, N. Kroupis, D. Soudris, A. Thanailakis
IEE Proceedings Vision Image and Signal Processing, 2004
Fast implementation of morphological operations using binary image block decomposition
BASILIOS GATOS, STAVROS J. PERANTONIS, NIKOS PAPAMARKOS, IOANNIS ANDREADIS
International Journal of Image and Graphics, 2004
A neuro-fuzzy technique for document binarisation
Nikos Papamarkos
Neural Computing and Applications, 2003
JPEG2000 over noisy communication channels thorough evaluation and cost analysis
G. Pavlidis, A. Tsompanopoulos, N. Papamarkos, C. Chamzas
Signal Processing Image Communication, 2003
Document gray-scale reduction using a neuro-fuzzy technique
NIKOS PAPAMARKOS
International Journal of Pattern Recognition and Artificial Intelligence, 2003
Exact image reconstruction using a limited number of projection samples
A.L. Kesidis, N. Papamarkos
International Symposium on Image and Signal Processing and Analysis Ispa, 2003
An intelligent hardware structure for impulse noise suppression
G. Louverdis, I. Andreadis, N. Papamarkos
International Symposium on Image and Signal Processing and Analysis Ispa, 2003
On estimation of the number of image principal colors and color reduction through self-organized neural networks
A. Atsalakis, N. Papamarkos, I. Andreadis
International Journal of Imaging Systems and Technology, 2002
Text extraction in complex color documents
C. Strouthopoulos, N. Papamarkos, A.E. Atsalakis
Pattern Recognition, 2002
Color image retrieval using a fractal signature extraction technique
N. Nikolaou, N. Papamarkos
Engineering Applications of Artificial Intelligence, 2002
Adaptive color reduction
N. Papamarkos, A.E. Atsalakis, C.P. Strouthopoulos
IEEE Transactions on Systems Man and Cybernetics Part B Cybernetics, 2002
Image retrieval using a fractal signature extraction technique
N. Nikolaou, N. Papamarkos
International Conference on Digital Signal Processing DSP, 2002
A window-based color quantization technique and its embedded implementation
IEEE International Conference on Image Processing, 2002
JPEG2000 over noisy communication channels the cost analysis aspect
IEEE International Conference on Image Processing, 2002
A window-based color quantization technique and its architecture implementation
A. Atsalakis, N. Kroupis, D. Soudris, N. Papamarkos
International Conference on Digital Signal Processing DSP, 2002
A Technique for Fuzzy Document Binarization
Nikos Papamarkos
Proceedings of the ACM Symposium on Document Engineering, 2001
Applying fast segmentation techniques at a binary image represented by a set of non-overlapping blocks
B. Gatos, N. Papamarkos
Proceedings of the International Conference on Document Analysis and Recognition ICDAR, 2001
New signature verification technique based on a two-stage neural network classifier
H. Baltzakis, N. Papamarkos
Engineering Applications of Artificial Intelligence, 2001
A window-based gray-scale inverse Hough transform algorithm and its applications on gray-scale line filtering
IEEE International Conference on Image Processing, 2001
A new adaptive color quantization technique
Antonios Atsalakis, Nikos Papamarkos, Charalambos Strouthopoulos
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2001
Histogram based color reduction through self-organized neural networks
Antonios Atsalakis, Ioannis Andreadis, Nikos Papamarkos
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2001
Locating text in color documents
IEEE International Conference on Image Processing, 2001
Using local features in a neural network based gray-level reduction technique
Proceedings International Conference on Pattern Recognition, 2000
On the approximation of real rational functions via mixed-integer linear programming
Nikos Papamarkos
Applied Mathematics and Computation, 2000
Multithresholding of mixed-type documents
C. Strouthopoulos, N. Papamarkos
Engineering Applications of Artificial Intelligence, 2000
On the gray-scale inverse Hough transform
A.L Kesidis, N Papamarkos
Image and Vision Computing, 2000
Colour image skeletonisation
European Signal Processing Conference, 2000
A window-based inverse Hough transform
A.L. Kesidis, N. Papamarkos
Pattern Recognition, 2000
Multithresholding of mixed-type documents
N. Papamarkos, C. Strouthopoulos
Proceedings IEEE International Symposium on Circuits and Systems, 2000
Gray-level reduction using local spatial features
Nikos Papamarkos, Antonios Atsalakis
Computer Vision and Image Understanding, 2000
Gray-scale Inverse Hough Transform algorithm
A.L. Kesidis, N. Papamarkos
Proceedings IEEE International Symposium on Circuits and Systems, 2000
Multithresholding of color and gray-level images through a neural network technique
N. Papamarkos, C. Strouthopoulos, I. Andreadis
Image and Vision Computing, 2000
Color reduction using local features and a Kohonen self-organized feature map neural network
Nikos Papamarkos
International Journal of Imaging Systems and Technology, 1999
Separation of overlapping characters
N. Papamarkos, T. Koutalianos
Proceedings of the IEEE International Conference on Electronics Circuits and Systems, 1999
Block decomposition and segmentation for fast Hough transform evaluation
Stavros J. Perantonis, Basilios Gatos, Nikos Papamarkos
Pattern Recognition, 1999
PLA using RLSA and a neural network
C. Strouthopoulos, N. Papamarkos, C. Chamzas
Engineering Applications of Artificial Intelligence, 1999
Text identification for document image analysis using a neural network
C. Strouthopoulos, N. Papamarkos
Image and Vision Computing, 1998
Document block identification using a neural network
International Conference on Digital Signal Processing DSP, 1997
Off-line signature verification using multiple neural network classification structures
International Conference on Digital Signal Processing DSP, 1997
Sampling on polar coordinates
International Conference on Digital Signal Processing DSP, 1997
Using curvature features in a multiclassifier OCR system
Basilios Gatos, Nikos Papamarkos, Christodoulos Chamzas
Engineering Applications of Artificial Intelligence, 1997
Identification of text-only areas in mixed-type documents
C. Strouthopoulos, N. Papamarkos, C. Chamzas
Engineering Applications of Artificial Intelligence, 1997
A binary-tree-based OCR technique for machine-printed characters
B. Gatos, N. Papamarkos, C. Chamzas
Engineering Applications of Artificial Intelligence, 1997
Skew detection and text line position determination in digitized documents
B. Gatos, N. Papamarkos, C. Chamzas
Pattern Recognition, 1997
A new approach for the design of digital integrators
N. Papamarkos, C. Chamzas
IEEE Transactions on Circuits and Systems I Fundamental Theory and Applications, 1996
Image segmentation and linear feature identification using rectangular block decomposition
Proceedings of the IEEE International Conference on Electronics Circuits and Systems, 1996
Determination of run-length smoothing values for document segmentation
Proceedings of the IEEE International Conference on Electronics Circuits and Systems, 1996
Accelerated Hough transform using rectangular image decomposition
B. Gatos, S.J. Perantonis, N. Papamarkos
Electronics Letters, 1996
Multirational function approximation via linear programming
Nikos Papamarkos
Applied Mathematics and Computation, 1996
On the development of an OCR system based on curvature features
IEEE International Symposium on Industrial Electronics, 1995
A New Approach for Multilevel Threshold Selection
N. Papamarkos, B. Gatos
CVGIP Graphical Models and Image Processing, 1994
On the design of 2D IIR digital filters using penalty optimization techniques
N. Papamarkos
International Journal of Circuit Theory and Applications, 1992
On the design of 1D IIR digital filters with coefficients of finite word length
N. Papamarkos, G. Vachtsevanos
International Journal of Circuit Theory and Applications, 1991
Time domain design of 1-D IIR digital filters with coefficients of finite word length
AMSE Review Association for the Advancement of Modelling and Simulation Techniques in Enterprises, 1990
On the approximation of the magnitude response of 1-D IIR digital filters using linear programming
AMSE Review Association for the Advancement of Modelling and Simulation Techniques in Enterprises, 1990
A fast linear programming approach to the design of 1D IIR digital filters
N. Papamarkos, G. Vachtsevanos
International Journal of Circuit Theory and Applications, 1990
Design of a microprocessor-based sphygmomanometer
Biomedical Instrumentation and Technology, 1990
A program for the optimum approximation of real rational functions via linear programming
N. Papamarkos
Advances in Engineering Software 1978, 1989
A program which implements a new algorithm for the solution of the linear minimax approximation problem
N. Papamarkos
Advances in Engineering Software 1978, 1989
Development of a microprocessor-based adaptive technique for blood pressure measurements
Medical Progress Through Technology, 1988
A New Algorithm for the Solution of the Linear Minimax Approximation Problem
N. Papamarkos, G. Vachtsevanos
Optimization, 1988
On the optimum approximation of real rational functions via linear programming
N. Papamarkos, G. Vachtsevanos, B. Mertzios
Applied Mathematics and Computation, 1988
On the approximation of the magnitude response of two-dimensional IIR digital filters using linear programming
G. Vachtsevanos, N. Papamarkos, B. Mertzios
Circuits Systems and Signal Processing, 1987
Design of two-dimensional IIR digital filters via linear programming
G Vachtsevanos, N Papamarkos, B Mertzios
Signal Processing, 1987
On the optimum design of symmetric two‐dimensional IIR digital filters with coefficients of finite word length
N. Papamarkos, B. Mertzios, G. Vachtsevanos
International Journal of Circuit Theory and Applications, 1986
ON THE APPROXIMATION OF THE MAGNITUDE RESPONSE OF 2-D IIR DIGITAL FILTERS USING LINEAR PROGRAMMING.
Proceedings IEEE International Symposium on Circuits and Systems, 1985
Design and development of a new electronic sphygmomanometer
G. J. Vachtsevanos, K. C. Kalaitzakis, N. E. Papamarkos
Medical Biological Engineering Computing, 1985
Correlation study of arterial blood pressure level to the amplitude of the pressure pulse waveform
G. Vachtsevanos, C. Kalaitzakis, N. Papamarkos, G. Ziakas, K. Economou, K. Gemitzis
Journal of Biomedical Engineering, 1984

Nikolaos Papamarkos

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