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ORCIDAdam Krzyzak
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- affiliation: Concordia University, Montreal, Canada
- affiliation: Westpomeranian University of Technology (WUT), Szczecin, Poland
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2020 – today
- 2024
[j80]Guangyi Chen
, Adam Krzyzak:
Wavelet-based 3D Data Cube Denoising Using Three Scales of Dependency. Circuits Syst. Signal Process. 43(6): 4010-4020 (2024)- [j79]Jeongik Cho, Adam Krzyzak:
Efficient integration of perceptual variational autoencoder into dynamic latent scale generative adversarial network. Expert Syst. J. Knowl. Eng. 41(10) (2024) - [j78]Adam Krzyzak, Jedrzej Wieckowski, Wojciech Rafajlowicz, Przemyslaw Moczko, Ewaryst Rafajlowicz:
Designing shape-preserving descriptors for classifying signals with application to vibrations of large mechanical structures. Knowl. Based Syst. 299: 112028 (2024) - [j77]Guang Yi Chen, Adam Krzyzak:
Face recognition via selective denoising, filter faces and hog features. Signal Image Video Process. 18(1): 369-378 (2024) - [j76]Guang Yi Chen, Adam Krzyzak:
Illumination invariant face recognition via multiscale filter faces and voting technique. Signal Image Video Process. 18(8-9): 5933-5938 (2024) - [c133]Karima Ben Suliman, Adam Krzyzak:
Vision Transformer Features-Based Leukemia Classification. ANNPR 2024: 111-120 - [c132]Farnaz Haghshenas, Adam Krzyzak, Stanislaw Osowski:
Comparative Study of Deep Learning Models in Melanoma Detection. ANNPR 2024: 121-131 - [c131]Guang Yi Chen, Adam Krzyzak, Ventzeslav Valev:
Palmprint Classification via Filter Faces and Feature Extraction. ANNPR 2024: 208-217 - [c130]Guangyi Chen, Wenfang Xie, Adam Krzyzak:
Hyperspectral Face Recognition via Existing 2D Face Recognition Methods. ICIC (5) 2024: 12-22 - [c129]Michael Kohler, Benjamin Walter, Adam Krzyzak:
Rate of Convergence of an Over-Parametrized Convolutional Neural Network Image Classifier Learned by Gradient Descent. ISIT 2024: 374-379 - [c128]Belal Nwiran, Adam Krzyzak:
MobileNetV3 Layer Sensitivity and Sparsity. SERP4IoT 2024: 38-43 - [e3]Ching Yee Suen, Adam Krzyzak, Mirco Ravanelli, Edmondo Trentin, Cem Subakan, Nicola Nobile:
Artificial Neural Networks in Pattern Recognition - 11th IAPR TC3 Workshop, ANNPR 2024, Montreal, QC, Canada, October 10-12, 2024, Proceedings. Lecture Notes in Computer Science 15154, Springer 2024, ISBN 978-3-031-71601-0 [contents] - [i5]Michael Kohler, Adam Krzyzak, Benjamin Walter:
Analysis of the rate of convergence of an over-parametrized convolutional neural network image classifier learned by gradient descent. CoRR abs/2405.07619 (2024) - 2023
- [j75]Mohammad Amin Shamshiri, Adam Krzyzak, Marek Kowal, Józef Korbicz:
Compatible-domain Transfer Learning for Breast Cancer Classification with Limited Annotated Data. Comput. Biol. Medicine 154: 106575 (2023) - [j74]Guangyi Chen, Adam Krzyzak:
Invariant Pattern Recognition with Log-Polar Transform and Dual-Tree Complex Wavelet-Fourier Features. Sensors 23(8): 3842 (2023) - [c127]Adam Krzyzak, Wojciech Rafajlowicz, Ewaryst Rafajlowicz:
Learning Bezier-Durrmeyer Type Descriptors for Classifying Curves - Preliminary Studies. ICAISC (1) 2023: 530-541 - [c126]Adam Krzyzak, Wojciech Rafajlowicz, Ewaryst Rafajlowicz:
Learning Shape-Preserving Autoencoder for the Reconstruction of Functional Data from Noisy Observations. ICCS (2) 2023: 264-272 - [c125]Guangyi Chen, Wenfang Xie, Adam Krzyzak:
Improved Blind Image Denoising with DnCNN. ICIC (2) 2023: 263-271 - [c124]Guangyi Chen, Wenfang Xie, Adam Krzyzak:
An Experimental Study on MRI Denoising with Existing Image Denoising Methods. ICIC (2) 2023: 429-437 - [c123]Guang Yi Chen, Adam Krzyzak, Ventzeslav Valev:
A Robust Preprocessing Method for Measuring Image Visual Quality Using Log-Polar FFT Features. IWAIPR 2023: 445-454 - [i4]Michael Kohler, Adam Krzyzak:
On the rate of convergence of an over-parametrized Transformer classifier learned by gradient descent. CoRR abs/2312.17007 (2023) - 2022
- [j73]Guangyi Chen, Adam Krzyzak, Shen-En Qian:
Hyperspectral imagery classification with minimum noise fraction, 2D spatial filtering and SVM. Int. J. Wavelets Multiresolution Inf. Process. 20(6): 2250025:1-2250025:13 (2022) - [j72]Guang Yi Chen, Adam Krzyzak, Piotr Duda, Andrzej Cader:
Noise Robust Illumination Invariant Face Recognition Via Bivariate Wavelet Shrinkage in Logarithm Domain. J. Artif. Intell. Soft Comput. Res. 12(3): 169-180 (2022) - [j71]Guang Yi Chen, Adam Krzyzak, Wen-Fang Xie:
Hyperspectral face recognition with histogram of oriented gradient features and collaborative representation-based classifier. Multim. Tools Appl. 81(2): 2299-2310 (2022) - [j70]Michael Kohler, Adam Krzyzak, Sophie Langer:
Estimation of a Function of Low Local Dimensionality by Deep Neural Networks. IEEE Trans. Inf. Theory 68(6): 4032-4042 (2022) - [c122]Adam Krzyzak, Tomasz Galkowski, Marian Partyka:
Convergence of RBF Networks Regression Function Estimates and Classifiers. ICAISC (1) 2022: 363-376 - [c121]Tomasz Galkowski, Adam Krzyzak, Piotr Dziwiñski:
Fast Estimation of Multidimensional Regression Functions. ICARCV 2022: 211-216 - [c120]Guangyi Chen, Wenfang Xie, Adam Krzyzak:
Illumination Invariant Face Recognition Using Directional Gradient Maps. ICIC (1) 2022: 330-338 - [c119]Tomasz Galkowski, Adam Krzyzak:
Fast Estimation of Multidimensional Regression Functions by the Parzen Kernel-Based Method. ICONIP (4) 2022: 251-262 - [c118]Vitaliy Tayanov, Adam Krzyzak, Ching Y. Suen:
Analysis of Different Deep Learning Architectures to Learn Generalised Classifier Stacking on Riemannian and Grassmann Manifolds. ICPR 2022: 2735-2741 - [c117]Manuel S. Lazo-Cortés, José Fco. Martínez-Trinidad, Jesús Ariel Carrasco-Ochoa, Ventzeslav Valev, Mohammad Amin Shamshiri, Adam Krzyzak:
Taking Advantage of Typical Testor Algorithms for Computing Non-reducible Descriptors. ICPRAM 2022: 188-194 - [c116]Jeongik Cho, Adam Krzyzak:
Dynamic Latent Scale for GAN Inversion. ICPRAM 2022: 221-228 - [c115]Guangyi Chen, Adam Krzyzak, Ventzeslav Valev:
A New Preprocessing Method for Measuring Image Visual Quality Robust to Rotation and Spatial Shifts. S+SSPR 2022: 94-102 - [c114]Jeongik Cho, Adam Krzyzak:
Self-supervised Out-of-Distribution Detection with Dynamic Latent Scale GAN. S+SSPR 2022: 113-121 - [c113]Naitik Bhise, Adam Krzyzak, Tien D. Bui:
Refining AttnGAN Using Attention on Attention Network. S+SSPR 2022: 283-291 - [e2]Adam Krzyzak, Ching Y. Suen, Andrea Torsello, Nicola Nobile:
Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshops, S+SSPR 2022, Montreal, QC, Canada, August 26-27, 2022, Proceedings. Lecture Notes in Computer Science 13813, Springer 2022, ISBN 978-3-031-23027-1 [contents] - 2021
- [j69]Vitaliy Tayanov, Adam Krzyzak, Ching Y. Suen:
Ensemble Learning Using Matrices of Classifier Interactions and Decision Profiles on Riemannian and Grassmann Manifolds. Int. J. Pattern Recognit. Artif. Intell. 35(12): 2160011:1-2160011:22 (2021) - [j68]Guangyi Chen, Adam Krzyzak:
An FFT-based visual quality metric robust to spatial shift. Int. J. Wavelets Multiresolution Inf. Process. 19(6): 2150024:1-2150024:11 (2021) - [j67]Guangyi Chen, Adam Krzyzak:
Noise reduction of shot-noise-dominated hyperspectral imagery by combining PCA with existing denoising methods. Int. J. Wavelets Multiresolution Inf. Process. 19(6): 2150028:1-2150028:20 (2021) - [j66]Tomasz Galkowski, Adam Krzyzak, Zofia Patora-Wysocka, Zbigniew Filutowicz, Lipo Wang:
A New Approach to Detection of Changes in Multidimensional Patterns - Part II. J. Artif. Intell. Soft Comput. Res. 11(3): 217-227 (2021) - [c112]Tomasz Galkowski, Adam Krzyzak:
Abrupt Change Detection by the Nonparametric Approach Based on Orthogonal Series Estimates. ICAISC (1) 2021: 318-327 - [c111]Adam Krzyzak, Heinrich Niemann:
Convergence properties of radial basis functions networks in function learning. KES 2021: 3761-3767 - 2020
- [j65]Tomasz Galkowski, Adam Krzyzak, Zbigniew Filutowicz:
A New Approach to Detection of Changes in Multidimensional Patterns. J. Artif. Intell. Soft Comput. Res. 10(2): 125-136 (2020) - [c110]Amr Shahin, Adam Krzyzak:
Genre-ous: The Movie Genre Detector. ACIIDS (Companion) 2020: 308-318 - [c109]Tomasz Galkowski, Adam Krzyzak:
A New Approach to Detection of Abrupt Changes in Black-and-White Images. ICAISC (2) 2020: 3-18 - [c108]Abdulrahman Aloyayri, Adam Krzyzak:
Breast Cancer Classification from Histopathological Images Using Transfer Learning and Deep Neural Networks. ICAISC (1) 2020: 491-502 - [c107]Varun Gupta, Adam Krzyzak:
An Empirical Evaluation of Attention and Pointer Networks for Paraphrase Generation. ICCS (3) 2020: 399-413 - [c106]Matthew Zak, Adam Krzyzak:
Classification of Lung Diseases Using Deep Learning Models. ICCS (3) 2020: 621-634 - [c105]Tomasz Galkowski, Adam Krzyzak:
Edge Curve Estimation by the Nonparametric Parzen Kernel Method. ICONIP (4) 2020: 377-385 - [c104]Nicola Yanev, Ventzeslav Valev, Karima Ben Suliman, Adam Krzyzak:
Supervised Classification Using Graph-based Space Partitioning for Multiclass Problems. ICPR 2020: 6486-6492 - [c103]Vitaliy Tayanov, Adam Krzyzak, Ching Y. Suen:
Comparison of Stacking-based Classifier Ensembles using Euclidean and Riemannian Geometries. ICPR 2020: 10359-10366 - [c102]Vitaliy Tayanov, Adam Krzyzak, Ching Y. Suen:
Manifold-Based Classifier Ensembles. ICPRAI 2020: 293-305 - [c101]Ellison Chan, Adam Krzyzak, Ching Y. Suen:
Predicting US Elections with Social Media and Neural Networks. ICPRAI 2020: 325-335 - [i3]Michael Kohler, Adam Krzyzak, Benjamin Walter:
On the rate of convergence of image classifiers based on convolutional neural networks. CoRR abs/2003.01526 (2020) - [i2]Michael Kohler, Adam Krzyzak:
On the rate of convergence of a deep recurrent neural network estimate in a regression problem with dependent data. CoRR abs/2011.00328 (2020)
2010 – 2019
- 2019
- [j64]Nicola Yanev, Ventzeslav Valev, Adam Krzyzak, Karima Ben Suliman:
Supervised classification using graph-based space partitioning. Pattern Recognit. Lett. 128: 122-130 (2019) - [j63]Michael Kohler, Adam Krzyzak:
Estimation of a Density From an Imperfect Simulation Model. IEEE Trans. Inf. Theory 65(3): 1535-1546 (2019) - [c100]Ventzeslav Valev, Nicola Yanev, Adam Krzyzak, Karima Ben Suliman:
Supervised Classification Box Algorithm Based on Graph Partitioning. CORES 2019: 276-285 - [c99]Adam Krzyzak, Marian Partyka:
On Learning and Convergence of RBF Networks in Regression Estimation and Classification. ICAISC (1) 2019: 131-142 - [c98]Bartosz Miselis, Thomas Fevens, Adam Krzyzak, Marek Kowal, Roman Monczak:
Deep Neural Networks for Breast Cancer Diagnosis: Fine Needle Biopsy Scenario. PCBBE 2019: 131-142 - [i1]Michael Kohler, Adam Krzyzak, Sophie Langer:
Deep Learning and MARS: A Connection. CoRR abs/1908.11140 (2019) - 2018
- [j62]Mina Yousefi, Adam Krzyzak, Ching Y. Suen:
Mass detection in digital breast tomosynthesis data using convolutional neural networks and multiple instance learning. Comput. Biol. Medicine 96: 283-293 (2018) - [j61]Guangyi Chen, Tien D. Bui, Adam Krzyzak:
Filter-based face recognition under varying illumination. IET Biom. 7(6): 628-635 (2018) - [j60]Michael Kohler, Adam Krzyzak:
Adaptive Estimation of Quantiles in a Simulation Model. IEEE Trans. Inf. Theory 64(1): 501-512 (2018) - [c97]Adam Krzyzak, Marian Partyka:
Learning and Convergence of the Normalized Radial Basis Functions Networks. ICAISC (1) 2018: 118-129 - [c96]Karima Ben Suliman, Adam Krzyzak:
Computerized Counting-Based System for Acute Lymphoblastic Leukemia Detection in Microscopic Blood Images. ICANN (2) 2018: 167-178 - [c95]Vitaliy Tayanov, Adam Krzyzak, Ching Y. Suen:
Prediction-based classification using learning on Riemannian manifolds. ICPR 2018: 591-596 - [c94]Jurek Z. Sasiadek, Steve Ulrich, Adam Krzyzak:
Trajectory Tracking and Nonparametric Identification of Flexible Space Robot Manipulators. MMAR 2018: 83-88 - [c93]Ventzeslav Valev, Nicola Yanev, Adam Krzyzak, Karima Ben Suliman:
Supervised Classification Using Feature Space Partitioning. S+SSPR 2018: 194-203 - 2017
- [j59]Augustin Kelava, Michael Kohler, Adam Krzyzak, Tim Fabian Schaffland:
Nonparametric estimation of a latent variable model. J. Multivar. Anal. 154: 112-134 (2017) - [j58]Benedikt Bauer, Luc Devroye, Michael Kohler, Adam Krzyzak, Harro Walk:
Nonparametric estimation of a function from noiseless observations at random points. J. Multivar. Anal. 160: 93-104 (2017) - [j57]Michael Kohler, Adam Krzyzak:
Nonparametric Regression Based on Hierarchical Interaction Models. IEEE Trans. Inf. Theory 63(3): 1620-1630 (2017) - [c92]Muneera Alsaedi, Thomas Fevens, Adam Krzyzak, Lukasz Jelen:
Cytological malignancy grading systems for fine needle aspiration biopsies of breast cancer. BIBM 2017: 705-709 - [c91]Vitaliy Tayanov, Adam Krzyzak, Ching Y. Suen:
Some Properties of Consensus-Based Classification. CORES 2017: 276-285 - [c90]Adam Krzyzak, Marian Partyka:
Convergence and Rates of Convergence of Recursive Radial Basis Functions Networks in Function Learning and Classification. ICAISC (1) 2017: 107-117 - [c89]Artur Starczewski, Adam Krzyzak:
A Study of Cluster Validity Indices for Real-Life Data. ICAISC (2) 2017: 148-158 - [c88]Artur Starczewski, Adam Krzyzak:
Improvement of the Validity Index for Determination of an Appropriate Data Partitioning. ICAISC (2) 2017: 159-170 - [c87]Vitaliy Tayanov, Adam Krzyzak, Ching Y. Suen:
Classification Boosting by Data Decomposition Using Consensus-Based Combination of Classifiers. ICIAR 2017: 408-415 - [c86]Jurek Z. Sasiadek, Steve Ulrich, Adam Krzyzak:
Direct fuzzy adaptive control and nonparametric identification of robot manipulator with elastic joints. MMAR 2017: 119-124 - 2016
- [j56]Lukasz Jelen, Adam Krzyzak, Thomas Fevens, Michal Jelen:
Influence of feature set reduction on breast cancer malignancy classification of fine needle aspiration biopsies. Comput. Biol. Medicine 79: 80-91 (2016) - [j55]Behnam Karimi, Adam Krzyzak:
A novel technique for detecting suspicious lesions in breast ultrasound images. Concurr. Comput. Pract. Exp. 28(7): 2237-2260 (2016) - [j54]Guangyi Chen, Tien D. Bui, Adam Krzyzak:
Sparse support vector machine for pattern recognition. Concurr. Comput. Pract. Exp. 28(7): 2261-2273 (2016) - [j53]Daniel Jones, Michael Kohler, Adam Krzyzak, Alexander Richter:
Empirical Comparison of Nonparametric Regression Estimates on Real Data. Commun. Stat. Simul. Comput. 45(7): 2309-2319 (2016) - [j52]Georg C. Enss, Michael Kohler, Adam Krzyzak, Roland Platz:
Nonparametric Quantile Estimation Based on Surrogate Models. IEEE Trans. Inf. Theory 62(10): 5727-5739 (2016) - [c85]Mohammad Reza Ebrahimi, Ching Y. Suen, Olga Ormandjieva, Adam Krzyzak:
Recognizing Predatory Chat Documents using Semi-supervised Anomaly Detection. Document Recognition and Retrieval 2016: 1-9 - [c84]Piotr Duda, Lena Pietruczuk, Maciej Jaworski, Adam Krzyzak:
On the Cesàro-Means-Based Orthogonal Series Approach to Learning Time-Varying Regression Functions. ICAISC (2) 2016: 37-48 - [c83]Artur Starczewski, Adam Krzyzak:
A Modification of the Silhouette Index for the Improvement of Cluster Validity Assessment. ICAISC (2) 2016: 114-124 - [c82]Ventzeslav Valev, Nicola Yanev, Adam Krzyzak:
A new geometrical approach for solving the supervised pattern recognition problem. ICPR 2016: 1648-1652 - [c81]Michael Kohler, Adam Krzyzak:
The rates of convergence of neural network estimates of hierarchical interaction regression models. ISIT 2016: 975-977 - [p6]Yanbin Lu, Mina Yousefi, John Ellenberger, Richard H. Moore, Daniel B. Kopans, Adam Krzyzak, Ching Y. Suen:
3D Tomosynthesis to Detect Breast cancer. Handbook of Pattern Recognition and Computer Vision 2016: 371-393 - [p5]Adam Krzyzak:
Recent Results on Nonparametric Quantile Estimation in a Simulation Model. Challenges in Computational Statistics and Data Mining 2016: 225-246 - 2015
- [j51]Tina Felber, Michael Kohler, Adam Krzyzak:
Adaptive Density Estimation From Data With Small Measurement Errors. IEEE Trans. Inf. Theory 61(6): 3446-3456 (2015) - [c80]Artur Starczewski, Adam Krzyzak:
Performance Evaluation of the Silhouette Index. ICAISC 2015: 49-58 - [c79]Tomasz Olas, Wojciech K. Mleczko, Robert K. Nowicki, Roman Wyrzykowski, Adam Krzyzak:
Adaptation of RBM Learning for Intel MIC Architecture. ICAISC (1) 2015: 90-101 - [c78]Jerzy Z. Sasiadek, Anthony Green, Adam Krzyzak:
Nonparametric recursive identification and control of a flexible joint robot manipulator. MMAR 2015: 563-572 - 2014
- [j50]Joseph Lin Chu, Adam Krzyzak:
The Recognition Of Partially Occluded Objects with Support Vector Machines, Convolutional Neural Networks and Deep Belief Networks. J. Artif. Intell. Soft Comput. Res. 4(1): 5-19 (2014) - [j49]Tomasz Bruzdzinski, Adam Krzyzak, Thomas Fevens, Lukasz Jelen:
Web-Based Framework For Breast Cancer Classification. J. Artif. Intell. Soft Comput. Res. 4(2): 149-162 (2014) - [c77]Joseph Lin Chu, Adam Krzyzak:
Analysis of Feature Maps Selection in Supervised Learning Using Convolutional Neural Networks. Canadian AI 2014: 59-70 - [c76]Mina Yousefi, Adam Krzyzak, Ching Y. Suen:
Convex Cardinality Restricted Boltzmann Machine and Its Application to Pattern Recognition. Canadian AI 2014: 369-374 - [c75]Mehdi Habibzadeh, Adam Krzyzak, Thomas Fevens:
Comparative Study of Feature Selection for White Blood Cell Differential Counts in Low Resolution Images. ANNPR 2014: 216-227 - [c74]Asai Asaithambi, Ventzeslav Valev, Adam Krzyzak, Vesna Zeljkovic:
A new approach for binary feature selection and combining classifiers. HPCS 2014: 681-687 - [c73]Joseph Lin Chu, Adam Krzyzak:
Application of Support Vector Machines, Convolutional Neural Networks and Deep Belief Networks to Recognition of Partially Occluded Objects. ICAISC (1) 2014: 34-46 - [c72]Behnam Karimi, Adam Krzyzak:
Computer-Aided System for Automatic Classification of Suspicious Lesions in Breast Ultrasound Images. ICAISC (2) 2014: 131-142 - [c71]Bartosz Krawczyk, Lukasz Jelen, Adam Krzyzak, Thomas Fevens:
One-Class Classification Decomposition for Imbalanced Classification of Breast Cancer Malignancy Data. ICAISC (1) 2014: 539-550 - [c70]Tina Felber, Michael Kohler, Adam Krzyzak:
Density estimation using real and artificial data. ISIT 2014: 1677-1681 - [c69]Jerzy Z. Sasiadek, Anthony Green, Steve Ulrich, Adam Krzyzak:
Nonparametric identification and control of flexible joint robot manipulator. MMAR 2014: 221-228 - 2013
- [j48]Behnam Karimi, Adam Krzyzak:
A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images. J. Artif. Intell. Soft Comput. Res. 3(4): 265 (2013) - [j47]Pawel Filipczuk, Thomas Fevens, Adam Krzyzak, Roman Monczak:
Computer-Aided Breast Cancer Diagnosis Based on the Analysis of Cytological Images of Fine Needle Biopsies. IEEE Trans. Medical Imaging 32(12): 2169-2178 (2013) - [c68]Ali Jannatpour, Adam Krzyzak, Douglas D. O'Shaughnessy:
A new approach to short-time harmonic analysis of tonal audio signals using harmonic sinusoidals. CCECE 2013: 1-6 - [c67]Mehdi Habibzadeh, Adam Krzyzak, Thomas Fevens:
White Blood Cell Differential Counts Using Convolutional Neural Networks for Low Resolution Images. ICAISC (2) 2013: 263-274 - [c66]Guangyi Chen, Tien D. Bui, Adam Krzyzak:
Sparse Support Vector Machine for pattern recognition. HPCS 2013: 601-606 - [c65]Guangyi Chen, Tien Dai Bui, Adam Krzyzak, Weihua Liu:
Support Vector Machine with Customized Kernel. ISNN (1) 2013: 258-264 - [c64]Guangyi Chen, Tien Dai Bui, Adam Krzyzak, Yongjia Zhao:
Invariant Object Recognition Using Radon and Fourier Transforms. ISNN (1) 2013: 650-656 - 2012
- [j46]Michael Kohler, Adam Krzyzak:
Nonparametric estimation of non-stationary velocity fields from 3D particle tracking velocimetry data. Comput. Stat. Data Anal. 56(6): 1566-1580 (2012) - [j45]Gérard Biau, Luc Devroye, Vida Dujmovic, Adam Krzyzak:
An affine invariant k-nearest neighbor regression estimate. J. Multivar. Anal. 112: 24-34 (2012) - [j44]Adam Krzyzak:
Editorial. Trans. Mach. Learn. Data Min. 5(1): 1-2 (2012) - [c63]Guangyi Chen, Tien Dai Bui, Adam Krzyzak, Stéphane Coulombe:
Adaptive video denoising using block matching 3-D filtering. CCECE 2012: 1-4 - [c62]Ewa Skubalska-Rafajlowicz, Adam Krzyzak, Ewaryst Rafajlowicz:
Dimensionality Reduction Using External Context in Pattern Recognition Problems with Ordered Labels. ICAISC (1) 2012: 430-438 - [c61]Mehdi Habibzadeh, Adam Krzyzak, Thomas Fevens:
Analysis of White Blood Cell Differential Counts Using Dual-Tree Complex Wavelet Transform and Support Vector Machine Classifier. ICCVG 2012: 414-422 - [c60]Bartosz Krawczyk, Lukasz Jelen, Adam Krzyzak, Thomas Fevens:
Oversampling Methods for Classification of Imbalanced Breast Cancer Malignancy Data. ICCVG 2012: 483-490 - [c59]Gérard Biau, Adam Krzyzak, Luc Devroye, Vida Dujmovic:
An affine invariant k-nearest neighbor regression estimate. ISIT 2012: 1445-1447 - [c58]Adam Krzyzak, Jerzy Z. Sasiadek, Steve Ulrich:
Nonparametric identification of robot flexible joint space manipulator. MMAR 2012: 172-177 - 2011
- [j43]Guangyi Chen, Tien D. Bui, Adam Krzyzak:
Denoising of Three-Dimensional Data Cube Using bivariate Wavelet Shrinking. Int. J. Pattern Recognit. Artif. Intell. 25(3): 403-413 (2011) - [j42]László Györfi, Adam Krzyzak:
Why L1 view and what is next? Kybernetika 47(6): 840-854 (2011) - [c57]Adam Krzyzak:
Radial Basis Function Networks with optimal kernels. ISIT 2011: 860-863 - [c56]Mehdi Habibzadeh, Adam Krzyzak, Thomas Fevens, Ali Sadr:
Counting of RBCs and WBCs in noisy normal blood smear microscopic images. Computer-Aided Diagnosis 2011: 79633I - [c55]Jerzy Z. Sasiadek, Mark J. Walker, Adam Krzyzak:
Accurate feature matching for autonomous vehicle navigation in urban environments. MMAR 2011: 68-73 - [p4]Adam Krzyzak, Thomas Fevens, Mehdi Habibzadeh, Lukasz Jelen:
Application of Pattern Recognition Techniques for the Analysis of Histopathological Images. Computer Recognition Systems 4 2011: 623-644 - 2010
- [c54]Adam Krzyzak, Ewaryst Rafajlowicz:
Pattern Recognition with Linearly Structured Labels Using Recursive Kernel Estimator. ICAISC (1) 2010: 422-429 - [c53]Guangyi Chen, Tien D. Bui, Adam Krzyzak:
Denoising of Three Dimensional Data Cube Using Bivariate Wavelet Shrinking. ICIAR (1) 2010: 45-51
2000 – 2009
- 2009
- [j41]Guangyi Chen, Tien D. Bui, Adam Krzyzak:
Invariant pattern recognition using radon, dual-tree complex wavelet and Fourier transforms. Pattern Recognit. 42(9): 2013-2019 (2009) - [c52]Aleksey Izmailov, Adam Krzyzak:
On Improving the Efficiency of Eigenface Using a Novel Facial Feature Localization. ICIAP 2009: 414-424 - [c51]Lorenzo Luciano, Adam Krzyzak:
Automated Multimodal Biometrics Using Face and Ear. ICIAR 2009: 451-460 - [c50]Michael Kohler, Adam Krzyzak, Harro Walk:
On application of nonparametric regression estimation to options pricing. ISIT 2009: 1579-1583 - [c49]Lukasz Jelen, Thomas Fevens, Adam Krzyzak:
Influence of nuclei segmentation on breast cancer malignancy classification. Computer-Aided Diagnosis 2009: 726014 - 2008
- [j40]Lukasz Jelen, Thomas Fevens, Adam Krzyzak:
Classification of Breast Cancer Malignancy Using Cytological Images of Fine Needle Aspiration Biopsies. Int. J. Appl. Math. Comput. Sci. 18(1): 75-83 (2008) - [j39]Joanna Rokita, Adam Krzyzak, Ching Y. Suen:
Multimodal Biometrics by Face and Hand Images Taken by a Cell Phone Camera. Int. J. Pattern Recognit. Artif. Intell. 22(3): 411-429 (2008) - [c48]Lukasz Jelen, Adam Krzyzak, Thomas Fevens:
Comparison of Pleomorphic and Structural Features Used for Breast Cancer Malignancy Classification. Canadian AI 2008: 138-149 - [c47]Adam Krzyzak, Dominik Schäfer:
Nonlinear Function Learning Using Radial Basis Function Networks: Convergence and Rates. ICAISC 2008: 101-110 - [c46]Joanna Rokita, Adam Krzyzak, Ching Y. Suen:
Cell Phones Personal Authentication Systems Using Multimodal Biometrics. ICIAR 2008: 1013-1022 - [c45]Wu Ding, Ching Y. Suen, Adam Krzyzak:
A new courtesy amount recognition module of a Check Reading System. ICPR 2008: 1-4 - [c44]Jian-xiong Dong, Ching Y. Suen, Adam Krzyzak:
Effective shrinkage of large multi-class linear svm models for text categorization. ICPR 2008: 1-4 - 2007
- [j38]Shuo Li, Thomas Fevens, Adam Krzyzak, Chao Jin, Song Li:
Semi-automatic computer aided lesion detection in dental X-rays using variational level set. Pattern Recognit. 40(10): 2861-2873 (2007) - [j37]Michael Kohler, Adam Krzyzak:
On the Rate of Convergence of Local Averaging Plug-In Classification Rules Under a Margin Condition. IEEE Trans. Inf. Theory 53(5): 1735-1742 (2007) - [c43]Shuo Li, Thomas Fevens, Adam Krzyzak, Chao Jin, Song Li:
Computer aided root lesion detection using level set and complex wavelets. Computer-Aided Diagnosis 2007: 65141M - 2006
- [j36]Shuo Li, Thomas Fevens, Adam Krzyzak, Song Li:
An automatic variational level set segmentation framework for computer aided dental X-rays analysis in clinical environments. Comput. Medical Imaging Graph. 30(2): 65-74 (2006) - [j35]Shuo Li, Thomas Fevens, Adam Krzyzak, Song Li:
Automatic clinical image segmentation using pathological modeling, PCA and SVM. Eng. Appl. Artif. Intell. 19(4): 403-410 (2006) - [j34]Guangyi Chen, Tien D. Bui, Adam Krzyzak:
Rotation invariant feature extraction using Ridgelet and Fourier transforms. Pattern Anal. Appl. 9(1): 83-93 (2006) - [c42]Adam Krzyzak, Dominik Schäfer:
Nonlinear Function Learning by the Normalized Radial Basis Function Networks. ICAISC 2006: 46-55 - [c41]Guangyi Chen, Tien D. Bui, Adam Krzyzak:
Palmprint Classification using Dual-Tree Complex Wavelets. ICIP 2006: 2645-2648 - [c40]Guangyi Chen, Tien D. Bui, Adam Krzyzak:
Invariant Ridgelet-Fourier Descriptor for Pattern Recognition. ICPR (2) 2006: 768-771 - [c39]Michael Kohler, Adam Krzyzak:
Rate of convergence of local averaging plug-in classification rules under margin condition. ISIT 2006: 2176-2179 - [c38]Shuo Li, Thomas Fevens, Adam Krzyzak, Chao Jin, Song Li:
Fast and Robust Clinical Triple-Region Image Segmentation Using One Level Set Function. MICCAI (2) 2006: 766-773 - 2005
- [j33]Guangyi Chen, Tien D. Bui, Adam Krzyzak:
Image denoising using neighbouring wavelet coefficients. Integr. Comput. Aided Eng. 12(1): 99-107 (2005) - [j32]Jian-xiong Dong, Adam Krzyzak, Ching Y. Suen:
Fast SVM Training Algorithm with Decomposition on Very Large Data Sets. IEEE Trans. Pattern Anal. Mach. Intell. 27(4): 603-618 (2005) - [j31]Guangyi Chen, Tien D. Bui, Adam Krzyzak:
Image denoising with neighbour dependency and customized wavelet and threshold. Pattern Recognit. 38(1): 115-124 (2005) - [j30]Guangyi Chen, Tien D. Bui, Adam Krzyzak:
Rotation invariant pattern recognition using ridgelets, wavelet cycle-spinning and Fourier features. Pattern Recognit. 38(12): 2314-2322 (2005) - [j29]Jian-xiong Dong, Adam Krzyzak, Ching Y. Suen:
An improved handwritten Chinese character recognition system using support vector machine. Pattern Recognit. Lett. 26(12): 1849-1856 (2005) - [j28]Adam Krzyzak, Dominik Schäfer:
Nonparametric regression estimation by normalized radial basis function networks. IEEE Trans. Inf. Theory 51(3): 1003-1010 (2005) - [c37]Jian-xiong Dong, Dominique Ponson, Adam Krzyzak, Ching Y. Suen:
Cursive word skew/slant corrections based on Radon transform. ICDAR 2005: 478-483 - [c36]Jian-xiong Dong, Ching Y. Suen, Adam Krzyzak:
Algorithms of fast SVM evaluation based on subspace projection. IJCNN 2005: 865-870 - [c35]Michael Kohler, Adam Krzyzak:
Rates of convergence for adaptive regression estimates with multiple hidden layer feedforward neural networks. ISIT 2005: 1436-1440 - [c34]Shuo Li, Thomas Fevens, Adam Krzyzak, Chao Jin, Song Li:
Toward Automatic Computer Aided Dental X-ray Analysis Using Level Set Method. MICCAI 2005: 670-678 - [c33]Shuo Li, Thomas Fevens, Adam Krzyzak, Song Li:
A level set segmentation for computer-aided dental x-ray analysis. Image Processing 2005 - [c32]Shuo Li, Thomas Fevens, Adam Krzyzak, Song Li:
Automatic Clinical Image Segmentation Using Pathological Modelling, PCA and SVM. MLDM 2005: 314-324 - [c31]Jian-xiong Dong, Adam Krzyzak, Ching Y. Suen, Dominique Ponson:
Low-Level Cursive Word Representation Based on Geometric Decomposition. MLDM 2005: 590-599 - 2004
- [c30]Shuo Li, Thomas Fevens, Adam Krzyzak:
A SVM-based framework for autonomous volumetric medical image segmentation using hierarchical and coupled level sets. CARS 2004: 207-212 - [c29]Adam Krzyzak, Ewa Skubalska-Rafajlowicz:
Combining Space-Filling Curves and Radial Basis Function Networks. ICAISC 2004: 229-234 - [c28]Guangyi Chen, Tien D. Bui, Adam Krzyzak:
Image denoising using neighbouring wavelet coefficients. ICASSP (2) 2004: 917-920 - [c27]Michael Kohler, Adam Krzyzak:
Adaptive regression estimation with multilayer feedforward neural networks. ISIT 2004: 467 - [c26]Shuo Li, Thomas Fevens, Adam Krzyzak:
Image Segmentation Adapted for Clinical Settings by Combining Pattern Classification and Level Sets. MICCAI (1) 2004: 160-167 - 2003
- [j27]Jian-xiong Dong, Ching Y. Suen, Adam Krzyzak:
A Fast SVM Training Algorithm. Int. J. Pattern Recognit. Artif. Intell. 17(3): 367-384 (2003) - [j26]Guangyi Chen, Tien D. Bui, Adam Krzyzak:
Contour-based handwritten numeral recognition using multiwavelets and neural networks. Pattern Recognit. 36(7): 1597-1604 (2003) - [j25]Miroslaw Pawlak, Ewaryst Rafajlowicz, Adam Krzyzak:
Postfiltering versus prefiltering for signal recovery from noisy samples. IEEE Trans. Inf. Theory 49(12): 3195-3212 (2003) - [c25]Jian-xiong Dong, Adam Krzyzak, Ching Y. Suen:
A Fast Parallel Optimization for Training Support Vector Machine. MLDM 2003: 96-105 - 2002
- [b1]László Györfi, Michael Kohler, Adam Krzyzak, Harro Walk:
A Distribution-Free Theory of Nonparametric Regression. Springer series in statistics, Springer 2002, ISBN 978-0-387-95441-7, pp. I-XVI, 1-647 - [j24]Balázs Kégl, Adam Krzyzak:
Piecewise Linear Skeletonization Using Principal Curves. IEEE Trans. Pattern Anal. Mach. Intell. 24(1): 59-74 (2002) - [j23]Jie Zhou, Adam Krzyzak, Ching Y. Suen:
Verification - a method of enhancing the recognizers of isolated and touching handwritten numerals. Pattern Recognit. 35(5): 1179-1189 (2002) - [c24]Jian-xiong Dong, Adam Krzyzak, Ching Y. Suen:
A Fast SVM Training Algorithm. SVM 2002: 53-67 - 2001
- [j22]Adam Krzyzak, Jerzy Z. Sasiadek, Balázs Kégl:
Non-parametric identification of dynamic non-linear systems by a Hermite Series Approach. Int. J. Syst. Sci. 32(10): 1261-1285 (2001) - [j21]Michael Kohler, Adam Krzyzak:
Nonparametric regression estimation using penalized least squares. IEEE Trans. Inf. Theory 47(7): 3054-3059 (2001) - [c23]Jian-xiong Dong, Adam Krzyzak, Ching Y. Suen:
A Multi-Net Local Learning Framework for Pattern Recognition. ICDAR 2001: 328-332 - [c22]Adam Krzyzak:
Nonlinear Function Learning and Classification Using Optimal Radial Basis Function Networks. MLDM 2001: 217-225 - [c21]Jian-xiong Dong, Adam Krzyzak, Ching Y. Suen:
Local Learning Framework for Recognition of Lowercase Handwritten Characters. MLDM 2001: 226-238 - 2000
- [j20]Balázs Kégl, Adam Krzyzak, Tamás Linder, Kenneth Zeger:
Learning and Design of Principal Curves. IEEE Trans. Pattern Anal. Mach. Intell. 22(3): 281-297 (2000) - [c20]Balázs Kégl, Adam Krzyzak, Heinrich Niemann:
Radial Basis Function Networks and Complexity Regularization in Function Learning and Classification. ICPR 2000: 2081-2086 - [c19]Balázs Kégl, Adam Krzyzak:
Piecewise Linear Skeletonization Using Principal Curves. ICPR 2000: 3135-3138
1990 – 1999
- 1999
- [j19]Jie Zhou, Qiang Gan, Adam Krzyzak, Ching Y. Suen:
Recognition of handwritten numerals by Quantum Neural Network with fuzzy features. Int. J. Document Anal. Recognit. 2(1): 30-36 (1999) - 1998
- [j18]Adam Krzyzak, Tamás Linder:
Radial basis function networks and complexity regularization in function learning. IEEE Trans. Neural Networks 9(2): 247-256 (1998) - [c18]Balázs Kégl, Adam Krzyzak, Heinrich Niemann:
Radial basis function networks in nonparametric classification and function learning. ICPR 1998: 565-570 - [c17]Balázs Kégl, Adam Krzyzak, Tamás Linder, Kenneth Zeger:
A Polygonal Line Algorithm for Constructing Principal Curves. NIPS 1998: 501-507 - 1997
- [j17]Adam Krzyzak, Ewaryst Rafajlowicz, Miroslaw Pawlak:
Moving average restoration of bandlimited signals from noisy observations. IEEE Trans. Signal Process. 45(12): 2967-2976 (1997) - [c16]Janusz Mazurek, Adam Krzyzak, Andrzej Cichocki:
Rates of convergence of the recursive radial basis function networks. ICASSP 1997: 3317-3320 - 1996
- [j16]Adam Krzyzak:
On nonparametric estimation of nonlinear dynamic systems by the Fourier series estimate. Signal Process. 52(3): 299-321 (1996) - [j15]Adam Krzyzak, Tamás Linder, Gábor Lugosi:
Nonparametric estimation and classification using radial basis function nets and empirical risk minimization. IEEE Trans. Neural Networks 7(2): 475-487 (1996) - [j14]Miroslaw Pawlak, Ewaryst Rafajlowicz, Adam Krzyzak:
Exponential weighting algorithms for reconstruction of bandlimited signals. IEEE Trans. Signal Process. 44(3): 538-545 (1996) - [c15]Ewa Skubalska-Rafajlowicz, Adam Krzyzak:
Fast k-NN classification rule using metric on space-filling curves. ICPR 1996: 121-125 - [c14]Adam Krzyzak, Tamás Linder:
Radial basis function networks and nonparametric classification: complexity regularization and rates of convergence. ICPR 1996: 650-653 - [c13]Adam Krzyzak, Tamás Linder:
Radial Basis Function Networks and Complexity Regularization in Function Learning. NIPS 1996: 197-203 - 1995
- [c12]Adam Krzyzak:
On optimal radial basis function nets and nonlinear function estimates. ICNN 1995: 265-269 - [c11]Adam Krzyzak, Stan Klasa, Lei Xu:
On L1 convergence rate of RBF networks and kernel regression estimators with applications in classification. ICNN 1995: 2243-2246 - [p3]Patrice Scattolin, Adam Krzyzak:
Handwriting Recognition Using Weighted Elastic Matching. Research in Computer and Robot Vision 1995: 367-395 - 1994
- [j13]Lei Xu, Adam Krzyzak, Alan L. Yuille:
On radial basis function nets and kernel regression: Statistical consistency, convergence rates, and receptive field size. Neural Networks 7(4): 609-628 (1994) - [j12]Xinming Yu, Tien Dai Bui, Adam Krzyzak:
Robust Estimation for Range Image Segmentation and Reconstruction. IEEE Trans. Pattern Anal. Mach. Intell. 16(5): 530-538 (1994) - [c10]Adam Krzyzak, Tamás Linder, Gábor Lugosi:
Nonparametric classification using radial basis function nets and empirical risk minimization. ICPR (2) 1994: 72-76 - [c9]Adam Krzyzak, Stan Klasa, Lei Xu:
On L1 convergence rate of RBF networks and kernel regression estimators with applications in classification. ICPR (2) 1994: 364-366 - [c8]Adam Krzyzak, Rolf Unbehauen:
On Estimation of Nonlinear Systems by Nonparametric Techniques. ISCAS 1994: 189-192 - 1993
- [j11]Lei Xu, Adam Krzyzak, Erkki Oja:
Rival penalized competitive learning for clustering analysis, RBF net, and curve detection. IEEE Trans. Neural Networks 4(4): 636-649 (1993) - [c7]Nick W. Strathy, Ching Y. Suen, Adam Krzyzak:
Segmentation of handwritten digits using contour features. ICDAR 1993: 577-580 - 1992
- [j10]Adam Krzyzak:
Global convergence of the recursive kernel regression estimates with applications in classification and nonlinear system estimation. IEEE Trans. Inf. Theory 38(4): 1323-1338 (1992) - [j9]Lei Xu, Adam Krzyzak, Ching Y. Suen:
Methods of combining multiple classifiers and their applications to handwriting recognition. IEEE Trans. Syst. Man Cybern. 22(3): 418-435 (1992) - [c6]Xinming Yu, Tien D. Bui, Adam Krzyzak:
Range image segmentation and fitting by residual consensus. CVPR 1992: 657-660 - [c5]Lei Xu, Adam Krzyzak, Erkki Oja:
Unsupervised and supervised classifications by rival penalized competitive learning. ICPR (2) 1992: 496-499 - 1991
- [j8]Lei Xu, Adam Krzyzak, Erkki Oja:
Neural Nets for Dual Subspace Pattern Recognition Method. Int. J. Neural Syst. 2(3): 169-184 (1991) - [j7]Adam Krzyzak:
On exponential bounds on the Bayes risk of the kernel classification rule. IEEE Trans. Inf. Theory 37(3): 490-499 (1991) - [p2]Adam Krzyzak, W. Dai, Ching Y. Suen:
On the Recognition of Handwritten Characters using Neural Networks. Pattern Recognition: Architectures, Algorithms and Applications 1991: 115-135 - 1990
- [j6]Adam Krzyzak:
On estimation of a class of nonlinear systems by the kernel regression estimate. IEEE Trans. Inf. Theory 36(1): 141-152 (1990) - [c4]Adam Krzyzak, W. Dai, Ching Y. Suen:
Classification of large set of handwritten characters using modified back propagation model. IJCNN 1990: 225-232 - [c3]P. Y. Zhu, Tony Kasvand, Adam Krzyzak:
Motion estimation based on point correspondence using neural network. IJCNN 1990: 869-874
1980 – 1989
- 1989
- [j5]Adam Krzyzak, Siu Yun Leung, Ching Y. Suen:
Reconstruction of two-dimensional patterns from Fourier descriptors. Mach. Vis. Appl. 2(3): 123-140 (1989) - [p1]Adam Krzyzak, H. El Buaeshi:
Classification of Digitized Curves Represented by Signatures and Fourier Descriptors. Computer Vision and Shape Recognition 1989: 241-260 - [e1]Adam Krzyzak, Tony Kasvand, Ching Y. Suen:
Computer Vision and Shape Recognition. World Scientific Series in Computer Science 14, World Scientific 1989, ISBN 978-9971-5-0862-3, pp. 1-464 [contents] - 1988
- [c2]Adam Krzyzak, Siu Yun Leung, Ching Y. Suen:
Reconstruction of two dimensional patterns by Fourier descriptors. ICPR 1988: 555-558 - [c1]Adam Krzyzak, Siu Yun Leung, Ching Y. Suen:
Fourier Descriptors of Two Dimensional Shapes - Reconstruction and Accuracy. MVA 1988: 199-202 - 1986
- [j4]Adam Krzyzak:
The rates of convergence of kernel regression estimates and classification rules. IEEE Trans. Inf. Theory 32(5): 668-679 (1986) - 1984
- [j3]Adam Krzyzak, Miroslaw Pawlak:
Distribution-free consistency of a nonparametric kernel regression estimate and classification. IEEE Trans. Inf. Theory 30(1): 78-81 (1984) - [j2]Adam Krzyzak, Miroslaw Pawlak:
Almost everywhere convergence of a recursive regression function estimate and classification. IEEE Trans. Inf. Theory 30(1): 91-93 (1984) - 1983
- [j1]Adam Krzyzak:
Classification procedures using multivariate variable kernel density estimate. Pattern Recognit. Lett. 1(5-6): 293-298 (1983)
Coauthor Index
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