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2020 – today
- 2024
[j16]Kamil Faber, Dominik Zurek, Marcin Pietron, Nathalie Japkowicz, Antonio Vergari
, Roberto Corizzo:
From MNIST to ImageNet and back: benchmarking continual curriculum learning. Mach. Learn. 113(10): 8137-8164 (2024)- [j15]Radoslaw Szostak, Marcin Pietron, Przemyslaw Wachniew, Miroslaw Zimnoch, Pawel Cwiakala:
Estimation of Small-Stream Water Surface Elevation Using UAV Photogrammetry and Deep Learning. Remote. Sens. 16(8): 1458 (2024) - [c25]Dominik Zurek, Marcin Pietron, Kamil Pietak, Kamil Faber:
A Deep Double Q-Learning as a SDLS support in solving LABS problem. ESANN 2024 - [c24]Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo, Anna Wójcik:
AD-NEv++ - The multi-architecture neuroevolution-based multivariate anomaly detection framework. GECCO Companion 2024: 607-610 - [c23]Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo:
Towards Efficient Deep Autoencoders for Multivariate Time Series Anomaly Detection. ICCS (3) 2024: 461-469 - [c22]Marcin Pietron, Rafal Olszowski, Jakub Gomulka:
Efficient Argument Classification with Compact Language Models and ChatGPT-4 Refinements. ICCCI (1) 2024: 249-262 - [i31]Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo:
Towards efficient deep autoencoders for multivariate time series anomaly detection. CoRR abs/2403.02429 (2024) - [i30]Marcin Pietron, Rafal Olszowski, Jakub Gomulka:
Efficient argument classification with compact language models and ChatGPT-4 refinements. CoRR abs/2403.15473 (2024) - [i29]Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo:
AD-NEv++ : The multi-architecture neuroevolution-based multivariate anomaly detection framework. CoRR abs/2404.07968 (2024) - [i28]Paul Gajewski, Dominik Zurek, Marcin Pietron, Kamil Faber:
Solving Multi-Goal Robotic Tasks with Decision Transformer. CoRR abs/2410.06347 (2024) - [i27]Marcin Pietron, Kamil Faber, Dominik Zurek, Roberto Corizzo:
TinySubNets: An efficient and low capacity continual learning strategy. CoRR abs/2412.10869 (2024) - 2023
- [j14]Marcin Pietron, Dominik Zurek, Bartlomiej Sniezynski:
Speedup deep learning models on GPU by taking advantage of efficient unstructured pruning and bit-width reduction. J. Comput. Sci. 67: 101971 (2023) - [c21]Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo:
Ada-QPacknet - Multi-Task Forget-Free Continual Learning with Quantization Driven Adaptive Pruning. ECAI 2023: 1882-1889 - [c20]Magdalena Stachon, Marcin Pietron:
Chosen Methods of Improving Small Object Recognition with Weak Recognizable Features. FICC (2) 2023: 270-285 - [c19]Dominik Zurek, Roberto Corizzo, Michal Karwatowski, Marcin Pietron, Kamil Faber:
Transformed-*: A domain-incremental lifelong learning scenario generation framework. IJCNN 2023: 1-10 - [i26]Krzysztof Stuglik, Piotr Listkiewicz, Mateusz Kulczyk, Marcin Pietron:
J-Parallelio - automatic parallelization framework for Java virtual machine code. CoRR abs/2303.08746 (2023) - [i25]Kamil Faber, Dominik Zurek, Marcin Pietron, Nathalie Japkowicz, Antonio Vergari, Roberto Corizzo:
From MNIST to ImageNet and Back: Benchmarking Continual Curriculum Learning. CoRR abs/2303.11076 (2023) - [i24]Jakub Grzeszczyk, Michal Karwatowski, Daria Lukasik, Maciej Wielgosz, Pawel Russek, Szymon Mazurek, Jakub Caputa, Rafal Fraczek, Anna Smiech, Ernest Jamro, Sebastian Koryciak, Agnieszka Dabrowska-Boruch, Marcin Pietron, Kazimierz Wiatr:
Segmentation of the veterinary cytological images for fast neoplastic tumors diagnosis. CoRR abs/2305.04332 (2023) - [i23]Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo:
AD-NEV: A Scalable Multi-level Neuroevolution Framework for Multivariate Anomaly Detection. CoRR abs/2305.16497 (2023) - [i22]Radoslaw Szostak, Marcin Pietron, Przemyslaw Wachniew, Miroslaw Zimnoch, Pawel Cwiakala:
Estimation of River Water Surface Elevation Using UAV Photogrammetry and Machine Learning. CoRR abs/2306.06118 (2023) - [i21]Jakub Caputa, Maciej Wielgosz, Daria Lukasik, Pawel Russek, Jakub Grzeszczyk, Michal Karwatowski, Szymon Mazurek, Rafal Fraczek, Anna Smiech, Ernest Jamro, Sebastian Koryciak, Agnieszka Dabrowska-Boruch, Marcin Pietron, Kazimierz Wiatr:
Using super-resolution for enhancing visual perception and segmentation performance in veterinary cytology. CoRR abs/2306.11848 (2023) - [i20]Krystian Strzalka, Szymon Mazurek, Maciej Wielgosz, Pawel Russek, Jakub Caputa, Daria Lukasik, Jan Krupinski, Jakub Grzeszczyk, Michal Karwatowski, Rafal Fraczek, Ernest Jamro, Marcin Pietron, Sebastian Koryciak, Agnieszka Dabrowska-Boruch, Kazimierz Wiatr:
Using simulation to calibrate real data acquisition in veterinary medicine. CoRR abs/2307.11695 (2023) - [i19]Jan Krupinski, Maciej Wielgosz, Szymon Mazurek, Krystian Strzalka, Pawel Russek, Jakub Caputa, Daria Lukasik, Jakub Grzeszczyk, Michal Karwatowski, Rafal Fraczek, Ernest Jamro, Marcin Pietron, Sebastian Koryciak, Agnieszka Dabrowska-Boruch, Kazimierz Wiatr:
Computer-Aided Cytology Diagnosis in Animals: CNN-Based Image Quality Assessment for Accurate Disease Classification. CoRR abs/2308.06055 (2023) - [i18]Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo:
Ada-QPacknet - adaptive pruning with bit width reduction as an efficient continual learning method without forgetting. CoRR abs/2308.07939 (2023) - 2022
- [c18]Szymon Mazurek, Maciej Wielgosz, Jakub Caputa, Rafal Fraczek, Michal Karwatowski, Jakub Grzeszczyk, Daria Lukasik, Anna Smiech, Pawel Russek, Ernest Jamro, Agnieszka Dabrowska-Boruch, Marcin Pietron, Sebastian Koryciak, Kazimierz Wiatr:
Canine age classification using Deep Learning as a step towards preventive medicine in animals. FedCSIS 2022: 169-172 - [c17]Dominik Zurek, Marcin Pietron, Kamil Pietak, Marek Kisiel-Dorohinicki:
A Deep Neural Network as a TABU Support in Solving LABS Problem. ICCS (1) 2022: 237-243 - [i17]Michal Karwatowski, Marcin Pietron:
Context based lemmatizer for Polish language. CoRR abs/2207.11565 (2022) - [i16]Magdalena Stachon, Marcin Pietron:
Chosen methods of improving object recognition of small objects with weak recognizable features. CoRR abs/2208.13591 (2022) - 2021
- [j13]Kamil Faber, Marcin Pietron, Dominik Zurek:
Ensemble Neuroevolution-Based Approach for Multivariate Time Series Anomaly Detection. Entropy 23(11): 1466 (2021) - [c16]Dominik Zurek, Kamil Pietak, Marcin Pietron, Marek Kisiel-Dorohinicki:
New Variants of SDLS Algorithm for LABS Problem Dedicated to GPGPU Architectures. ICCS (1) 2021: 206-212 - [c15]Dominik Zurek, Marcin Pietron, Kazimierz Wiatr:
Accelerating Deep Convolutional Neural on GPGPU. SAI (2) 2021: 712-724 - [i15]Kamil Faber, Dominik Zurek, Marcin Pietron, Kamil Pietak:
Ensemble neuroevolution based approach for multivariate time series anomaly detection. CoRR abs/2108.03585 (2021) - [i14]Marcin Pietron, Dominik Zurek, Kamil Faber:
Fast and scalable neuroevolution deep learning architecture search for multivariate anomaly detection. CoRR abs/2112.05640 (2021) - [i13]Radoslaw Szostak, Marcin Pietron, Miroslaw Zimnoch, Przemyslaw Wachniew, Pawel Cwiakala, Edyta Puniach:
Neuroevolution deep learning architecture search for estimation of river surface elevation from photogrammetric Digital Surface Models. CoRR abs/2112.12510 (2021) - [i12]Marcin Pietron, Dominik Zurek:
Speedup deep learning models on GPU by taking advantage of efficient unstructured pruning and bit-width reduction. CoRR abs/2112.15445 (2021) - 2020
- [j12]Krzysztof Wróbel, Michal Karwatowski, Maciej Wielgosz, Marcin Pietron, Kazimierz Wiatr:
Compression of Convolutional Neural Network for Natural Language Processing. Comput. Sci. 21(1) (2020) - [j11]Mo'taz Al-Hami, Marcin Pietron, Raúl A. Casas, Maciej Wielgosz:
Methodologies of Compressing a Stable Performance Convolutional Neural Networks in Image Classification. Neural Process. Lett. 51(1): 105-127 (2020) - [c14]Marcin Pietron, Maciej Wielgosz:
Retrain or Not Retrain? - Efficient Pruning Methods of Deep CNN Networks. ICCS (3) 2020: 452-463 - [i11]Marcin Pietron, Maciej Wielgosz:
Retrain or not retrain? - efficient pruning methods of deep CNN networks. CoRR abs/2002.07051 (2020) - [i10]Dominik Zurek, Marcin Pietron:
Training with reduced precision of a support vector machine model for text classification. CoRR abs/2007.08657 (2020) - [i9]Marcin Pietron, Dominik Zurek:
When deep learning models on GPU can be accelerated by taking advantage of unstructured sparsity. CoRR abs/2011.06295 (2020)
2010 – 2019
- 2019
- [j10]Kamil Pietak, Dominik Zurek, Marcin Pietron, Andrzej Dymara, Marek Kisiel-Dorohinicki:
Striving for performance of discrete optimisation via memetic agent-based systems in a hybrid CPU/GPU environment. J. Comput. Sci. 31: 151-162 (2019) - [c13]Marcin Pietron, Michal Karwatowski, Maciej Wielgosz, Jerzy Duda:
Fast Compression and Optimization of Deep Learning Models for Natural Language Processing. CANDAR Workshops 2019: 162-168 - [c12]Anna Aniol, Marcin Pietron, Jerzy Duda:
Ensemble Approach for Natural Language Question Answering Problem. CANDAR Workshops 2019: 180-183 - [c11]Iwona Skalna, Marcin Pietron, Milan Hladík:
Improvements of Monotonicity Approach to Solve Interval Parametric Linear Systems. PPAM (2) 2019: 374-383 - [i8]Anna Aniol, Marcin Pietron:
Ensemble approach for natural language question answering problem. CoRR abs/1908.09720 (2019) - 2018
- [j9]Maciej Wielgosz, Michal Karwatowski, Marcin Pietron, Kazimierz Wiatr:
FPGA Implementation of Procedures for Video Quality Assessment. Comput. Sci. 19(3) (2018) - [c10]Krzysztof Wróbel, Maciej Wielgosz, Marcin Pietron, Michal Karwatowski, Jerzy Duda, Aleksander Smywinski-Pohl:
Improving Text Classification with Vectors of Reduced Precision. ICAART (2) 2018: 531-538 - [c9]Mo'taz Al-Hami, Marcin Pietron, Raúl A. Casas, Samer L. Hijazi, Piyush Kaul:
Towards a Stable Quantized Convolutional Neural Networks: An Embedded Perspective. ICAART (2) 2018: 573-580 - [i7]Krzysztof Wróbel, Marcin Pietron, Maciej Wielgosz, Michal Karwatowski, Kazimierz Wiatr:
Convolutional neural network compression for natural language processing. CoRR abs/1805.10796 (2018) - [i6]Mo'taz Al-Hami, Marcin Pietron, Rishi Kumar, Raúl A. Casas, Samer L. Hijazi, Chris Rowen:
Method for Hybrid Precision Convolutional Neural Network Representation. CoRR abs/1807.09760 (2018) - 2017
- [j8]Maciej Wielgosz, Rafal Fraczek, Pawel Russek, Marcin Pietron, Agnieszka Dabrowska-Boruch, Ernest Jamro, Kazimierz Wiatr:
Experiment on Methods for Clustering and Categorization of Polish Text. Comput. Informatics 36(1): 186-204 (2017) - [j7]Maciej Wielgosz, Pawel Szczepka, Pawel Russek, Ernest Jamro, Kazimierz Wiatr, Marcin Pietron, Dominik Zurek:
Evaluation and Implementation of n-Gram-Based Algorithm for Fast Text Comparison. Comput. Informatics 36(4): 887-907 (2017) - [j6]Maciej Wielgosz, Marcin Pietron:
Using Spatial Pooler of Hierarchical Temporal Memory to classify noisy videos with predefined complexity. Neurocomputing 240: 84-97 (2017) - [j5]Andrzej Glowacz, Marcin Pietron:
Implementation of Digital Watermarking Algorithms in Parallel Hardware Accelerators. Int. J. Parallel Program. 45(5): 1108-1127 (2017) - [j4]Marcin Pietron, Aleksander Byrski, Marek Kisiel-Dorohinicki:
Leveraging heterogeneous parallel platform in solving hard discrete optimization problems with metaheuristics. J. Comput. Sci. 18: 59-68 (2017) - [c8]Dominik Zurek, Kamil Pietak, Marcin Pietron, Marek Kisiel-Dorohinicki:
Toward hybrid platform for evolutionary computations of hard discrete problems. ICCS 2017: 877-886 - [i5]Krzysztof Wróbel, Maciej Wielgosz, Marcin Pietron, Michal Karwatowski, Aleksander Smywinski-Pohl:
Improving text classification with vectors of reduced precision. CoRR abs/1706.06363 (2017) - 2016
- [c7]Maciej Wielgosz, Marcin Pietron, Kazimierz Wiatr:
Using Spatial Pooler of Hierarchical Temporal Memory for object classification in noisy video streams. FedCSIS 2016: 271-274 - [c6]Marcin Pietron, Maciej Wielgosz, Pawel Russek, Kazimierz Wiatr:
Study of the Parallel Techniques for Dimensionality Reduction and Its Impact on Performance of the Text Processing Algorithms. ICAART (1) 2016: 315-322 - [c5]Marcin Pietron, Maciej Wielgosz, Kazimierz Wiatr:
Parallel Implementation of Spatial Pooler in Hierarchical Temporal Memory. ICAART (2) 2016: 346-353 - [c4]Krzysztof Wróbel, Maciej Wielgosz, Aleksander Smywinski-Pohl, Marcin Pietron:
Comparison of SVM and Ontology-Based Text Classification Methods. ICAISC (1) 2016: 667-680 - [c3]Marcin Pietron, Maciej Wielgosz, Kazimierz Wiatr:
Formal Analysis of HTM Spatial Pooler Performance Under Predefined Operation Conditions. IJCRS 2016: 396-405 - [i4]Marcin Pietron, Maciej Wielgosz, Kazimierz Wiatr:
Formal analysis of HTM Spatial Pooler performance under predefined operation conditions. CoRR abs/1607.00791 (2016) - [i3]Maciej Wielgosz, Marcin Pietron:
OpenCL-accelerated object classification in video streams using Spatial Pooler of Hierarchical Temporal Memory. CoRR abs/1608.01966 (2016) - [i2]Maciej Wielgosz, Marcin Pietron:
Noisy video classification with Spatial Pooler of Hierarchical Temporal Memory. CoRR abs/1609.03093 (2016) - [i1]Maciej Wielgosz, Michal Karwatowski, Marcin Pietron, Kazimierz Wiatr:
FPGA implementation of the procedures for video quality assessment. CoRR abs/1609.06109 (2016) - 2015
- [c2]Marcin Pietron, Aleksander Byrski, Marek Kisiel-Dorohinicki:
GPGPU for Difficult Black-box Problems. ICCS 2015: 1023-1032 - 2014
- [p1]Maciej Wielgosz, Marcin Janiszewski, Pawel Russek, Marcin Pietron, Ernest Jamro, Kazimierz Wiatr:
Implementation of a System for Fast Text Search and Document Comparison. Intelligent Tools for Building a Scientific Information Platform 2014: 173-186 - 2013
- [j3]Marcin Pietron, Pawel Russek, Kazimierz Wiatr:
Accelerating Select where and Select Join Queries on a GPU. Comput. Sci. 14(2): 243-252 (2013) - [j2]Dominik Zurek, Marcin Pietron, Maciej Wielgosz, Kazimierz Wiatr:
Comparison of Hybrid Sorting Algorithms Implemented on Different Parallel Hardware Platforms. Comput. Sci. 14(4): 679-691 (2013) - [c1]Marcin Pietron, Maciej Wielgosz, Dominik Zurek, Ernest Jamro, Kazimierz Wiatr:
Comparison of GPU and FPGA Implementation of SVM Algorithm for Fast Image Segmentation. ARCS 2013: 292-302 - 2010
- [j1]Marcin Pietron, Pawel Russek, Kazimierz Wiatr:
Loop profiling tool for HPC code inspection as an efficient method of FPGA based acceleration. Int. J. Appl. Math. Comput. Sci. 20(3): 581-589 (2010)
Coauthor Index
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