FPGA Implementation of Strongly Parallel Histogram Equalization. - Ernest Jamro; Maciej Wielgosz; Kazimierz Wiatr (DDECS, 2007)

FPGA Implementation of 64-bit Exponential Function for HPC. - Ernest Jamro; Kazimierz Wiatr; Maciej Wielgosz (FPL, 2007)

Highly efficient structure of 64-bit exponential function implemented in FPGAs. - Maciej Wielgosz; Ernest Jamro; Kazimierz Wiatr (ARC, 2008)

Computation Acceleration on SGI RASC: FPGA Based Reconfigurable Computing Hardware. - Ernest Jamro; Marcin Janiszewski; Krzysztof Machaczek; Pawel Russek; Kazimierz Wiatr; Maciej Wielgosz (Comput. Sci., 2008)

Accelerating Calculations on the RASC Platform: A Case Study of the Exponential Function. - Maciej Wielgosz; Ernest Jamro; Kazimierz Wiatr (ARC, 2009)

Hardware Implementation of the Exponent Based Computational Core for an Exchange-Correlation Potential Matrix Generation. - Maciej Wielgosz; Ernest Jamro; Kazimierz Wiatr (PPAM (1), 2009)

Highly Efficient Twin Module Structure of 64-Bit Exponential Function Implemented on SGI RASC Platform. - Maciej Wielgosz; Ernest Jamro; Kazimierz Wiatr (Comput. Informatics, 2009)

Hardware Implementation of the Orbital Function for Quantum Chemistry Calculations. - Maciej Wielgosz; Ernest Jamro; Pawel Russek; Kazimierz Wiatr (ARC, 2010)

Analysis of the Basic Implementation Aspects of Hardware-Accelerated Density Functional Theory Calculations. - Maciej Wielgosz; Grzegorz Mazur; Marcin Makowski; Ernest Jamro; Kazimierz Wiatr (Comput. Informatics, 2010)

The implementation of the customized, parallel architecture for a fast word-match program. - Ernest Jamro; Pawel Russek; Agnieszka Dabrowska-Boruch; Maciej Wielgosz; Kazimierz Wiatr (Comput. Syst. Sci. Eng., 2011)

FPGA-Based Platform for Real-Time Internet. - Maciej Wielgosz; Mauritz Panggabean; Ameen Chilwan; Leif Arne Rønningen (EST, 2012)

FPGA Implementation of the Selected Parts of the Fast Image Segmentation. - Maciej Wielgosz; Ernest Jamro; Dominik Zurek; Kazimierz Wiatr (Intelligent Tools for Building a Scientific Information Platform, 2012)

Comparison of GPU and FPGA Implementation of SVM Algorithm for Fast Image Segmentation. - Marcin Pietron; Maciej Wielgosz; Dominik Zurek; Ernest Jamro; Kazimierz Wiatr (ARCS, 2013)

Comparison of Hybrid Sorting Algorithms Implemented on Different Parallel Hardware Platforms. - Dominik Zurek; Marcin Pietron; Maciej Wielgosz; Kazimierz Wiatr (Comput. Sci., 2013)

An FPGA-Based Platform for a Network Architecture with Delay Guarantee. - Maciej Wielgosz; Mauritz Panggabean; Jiang Wang; Leif Arne Rønningen (J. Circuits Syst. Comput., 2013)

Implementation of a System for Fast Text Search and Document Comparison. - Maciej Wielgosz; Marcin Janiszewski; Pawel Russek; Marcin Pietron; Ernest Jamro; Kazimierz Wiatr (Intelligent Tools for Building a Scientific Information Platform, 2014)

Energy Efficient Calculations of Text Similarity Measure on FPGA-Accelerated Computing Platforms. - Michal Karwatowski; Pawel Russek; Maciej Wielgosz; Sebastian Koryciak; Kazimierz Wiatr (PPAM (1), 2015)

Using Spatial Pooler of Hierarchical Temporal Memory for object classification in noisy video streams. - Maciej Wielgosz; Marcin Pietron; Kazimierz Wiatr (FedCSIS, 2016)

Study of the Parallel Techniques for Dimensionality Reduction and Its Impact on Performance of the Text Processing Algorithms. - Marcin Pietron; Maciej Wielgosz; Pawel Russek; Kazimierz Wiatr (ICAART (1), 2016)

Parallel Implementation of Spatial Pooler in Hierarchical Temporal Memory. - Marcin Pietron; Maciej Wielgosz; Kazimierz Wiatr (ICAART (2), 2016)

Comparison of SVM and Ontology-Based Text Classification Methods. - Krzysztof Wróbel 002; Maciej Wielgosz; Aleksander Smywinski-Pohl; Marcin Pietron (ICAISC (1), 2016)

Formal Analysis of HTM Spatial Pooler Performance Under Predefined Operation Conditions. - Marcin Pietron; Maciej Wielgosz; Kazimierz Wiatr (IJCRS, 2016)

A Conceptual Development of Quench Prediction App build on LSTM and ELQA framework. - Matej Mertik; Maciej Wielgosz; Andrzej Skoczen (CoRR, 2016)

The observer-assisted method for adjusting hyper-parameters in deep learning algorithms. - Maciej Wielgosz (CoRR, 2016)

OpenCL-accelerated object classification in video streams using Spatial Pooler of Hierarchical Temporal Memory. - Maciej Wielgosz; Marcin Pietron (CoRR, 2016)

Noisy video classification with Spatial Pooler of Hierarchical Temporal Memory. - Maciej Wielgosz; Marcin Pietron (CoRR, 2016)

Using LSTM recurrent neural networks for detecting anomalous behavior of LHC superconducting magnets. - Maciej Wielgosz; Andrzej Skoczen; Matej Mertik (CoRR, 2016)

Semantic search extension based on polish wordnet relations in business document exploration. - Piotr Potiopa; Michal Karwatowski; Jerzy Duda; Pawel Sasor; Maciej Wielgosz; Bartlomiej Muzykiewicz (IML, 2017)

Experiment on Methods for Clustering and Categorization of Polish Text. - Maciej Wielgosz; Rafal Fraczek; Pawel Russek; Marcin Pietron; Agnieszka Dabrowska-Boruch; Ernest Jamro; Kazimierz Wiatr (Comput. Informatics, 2017)

Evaluation and Implementation of n-Gram-Based Algorithm for Fast Text Comparison. - Maciej Wielgosz; Pawel Szczepka; Pawel Russek; Ernest Jamro; Kazimierz Wiatr; Marcin Pietron; Dominik Zurek (Comput. Informatics, 2017)

A Conceptual Framework for Supporting a Rapid Design of Web Applications for Data Analysis of Electrical Quality Assurance Data for the LHC. - Matej Mertik; Maciej Wielgosz (CoRR, 2017)

Recurrent Neural Networks for anomaly detection in the Post-Mortem time series of LHC superconducting magnets. - Maciej Wielgosz; Andrzej Skoczen; Matej Mertik (CoRR, 2017)

Improving text classification with vectors of reduced precision. - Krzysztof Wróbel 002; Maciej Wielgosz; Marcin Pietron; Michal Karwatowski; Aleksander Smywinski-Pohl (CoRR, 2017)

The prototype of the HL-LHC magnets monitoring system based on Recurrent Neural Networks and adaptive quantization. - Maciej Wielgosz; Matej Mertik; Andrzej Skoczen (CoRR, 2017)

Using Spatial Pooler of Hierarchical Temporal Memory to classify noisy videos with predefined complexity. - Maciej Wielgosz; Marcin Pietron (Neurocomputing, 2017)

Improving Text Classification with Vectors of Reduced Precision. - Krzysztof Wróbel 002; Maciej Wielgosz; Marcin Pietron; Michal Karwatowski; Jerzy Duda; Aleksander Smywinski-Pohl (ICAART (2), 2018)

FPGA Implementation of Procedures for Video Quality Assessment. - Maciej Wielgosz; Michal Karwatowski; Marcin Pietron; Kazimierz Wiatr (Comput. Sci., 2018)

Convolutional neural network compression for natural language processing. - Krzysztof Wróbel 002; Marcin Pietron; Maciej Wielgosz; Michal Karwatowski; Kazimierz Wiatr (CoRR, 2018)

The model of an anomaly detector for HiLumi LHC magnets based on Recurrent Neural Networks and adaptive quantization. - Maciej Wielgosz; Matej Mertik; Andrzej Skoczen; Ernesto De Matteis (Eng. Appl. Artif. Intell., 2018)

Protection of Superconducting Industrial Machinery Using RNN-Based Anomaly Detection for Implementation in Smart Sensor. - Maciej Wielgosz; Andrzej Skoczen; Ernesto De Matteis (Sensors, 2018)

Fast Compression and Optimization of Deep Learning Models for Natural Language Processing. - Marcin Pietron; Michal Karwatowski; Maciej Wielgosz; Jerzy Duda (CANDAR Workshops, 2019)

Predictive Maintenance of Induction Motors Using Ultra-Low Power Wireless Sensors and Compressed Recurrent Neural Networks. - Michal Markiewicz; Maciej Wielgosz; Mikollaj Bochenski; Waldemar Tabaczynski; Tomasz Konieczny; Liliana Kowalczyk (IEEE Access, 2019)

Using Neural Networks with data Quantization for time Series Analysis in LHC Superconducting Magnets. - Maciej Wielgosz; Andrzej Skoczen (Int. J. Appl. Math. Comput. Sci., 2019)

Falls Prediction in eldery people using Gated Recurrent Units. - Marcin Radzio; Maciej Wielgosz; Matej Mertik (CoRR, 2019)

Mapping Neural Networks to FPGA-Based IoT Devices for Ultra-Low Latency Processing. - Maciej Wielgosz; Michal Karwatowski (Sensors, 2019)

Retrain or Not Retrain? - Efficient Pruning Methods of Deep CNN Networks. - Marcin Pietron; Maciej Wielgosz (ICCS (3), 2020)

Compression of Convolutional Neural Network for Natural Language Processing. - Krzysztof Wróbel 002; Michal Karwatowski; Maciej Wielgosz; Marcin Pietron; Kazimierz Wiatr (Comput. Sci., 2020)

Methodologies of Compressing a Stable Performance Convolutional Neural Networks in Image Classification. - Mo'taz Al-Hami; Marcin Pietron; Raúl A. Casas; Maciej Wielgosz (Neural Process. Lett., 2020)

Modern Cybersecurity Solution using Supervised Machine Learning. - Mustafa Sakhai; Maciej Wielgosz (CoRR, 2021)

Canine age classification using Deep Learning as a step towards preventive medicine in animals. - 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; et al. (FedCSIS, 2022)

Towards End-to-End Chase in Urban Autonomous Driving Using Reinforcement Learning. - Michal Kolomanski; Mustafa Sakhai; Jakub Nowak; Maciej Wielgosz (IntelliSys (3), 2022)

Towards End-to-End Escape in Urban Autonomous Driving Using Reinforcement Learning. - Mustafa Sakhai; Maciej Wielgosz (IntelliSys (2), 2023)

Synthetic Data Generation Framework, Dataset, and Efficient Deep Model for Pedestrian Intention Prediction. - Muhammad Naveed Riaz; Maciej Wielgosz; Abel Garcia Romera; Antonio M. López 001 (ITSC, 2023)

CARLA-BSP: a simulated dataset with pedestrians. - Maciej Wielgosz; Antonio M. López 001; Muhammad Naveed Riaz (CoRR, 2023)

Segmentation of the veterinary cytological images for fast neoplastic tumors diagnosis. - 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; et al. (CoRR, 2023)

Using super-resolution for enhancing visual perception and segmentation performance in veterinary cytology. - 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; et al. (CoRR, 2023)

Assessing Dataset Quality Through Decision Tree Characteristics in Autoencoder-Processed Spaces. - Szymon Mazurek; Maciej Wielgosz (CoRR, 2023)

Using simulation to calibrate real data acquisition in veterinary medicine. - Krystian Strzalka; Szymon Mazurek; Maciej Wielgosz; Pawel Russek; Jakub Caputa; Daria Lukasik; Jan Krupinski; Jakub Grzeszczyk; Michal Karwatowski; Rafal Fraczek; Ernest Jamro; Marcin Pietron; et al. (CoRR, 2023)

Computer-Aided Cytology Diagnosis in Animals: CNN-Based Image Quality Assessment for Accurate Disease Classification. - Jan Krupinski; Maciej Wielgosz; Szymon Mazurek; Krystian Strzalka; Pawel Russek; Jakub Caputa; Daria Lukasik; Jakub Grzeszczyk; Michal Karwatowski; Rafal Fraczek; Ernest Jamro; Marcin Pietron; et al. (CoRR, 2023)

FOR-instance: a UAV laser scanning benchmark dataset for semantic and instance segmentation of individual trees. - Stefano Puliti; Grant D. Pearse; Peter Surový; Luke Wallace; Markus Hollaus; Maciej Wielgosz; Rasmus Astrup (CoRR, 2023)

Automated forest inventory: analysis of high-density airborne LiDAR point clouds with 3D deep learning. - Binbin Xiang; Maciej Wielgosz; Theodora Kontogianni; Torben Peters; Stefano Puliti; Rasmus Astrup; Konrad Schindler (CoRR, 2023)

Point2Tree(P2T) - Framework for Parameter Tuning of Semantic and Instance Segmentation Used with Mobile Laser Scanning Data in Coniferous Forest. - Maciej Wielgosz; Stefano Puliti; Phil Wilkes; Rasmus Astrup (Remote. Sens., 2023)

SegmentAnyTree: A sensor and platform agnostic deep learning model for tree segmentation using laser scanning data. - Maciej Wielgosz; Stefano Puliti; Binbin Xiang; Konrad Schindler; Rasmus Astrup (CoRR, 2024)

Pedestrian intention prediction in Adverse Weather Conditions with Spiking Neural Networks and Dynamic Vision Sensors. - Mustafa Sakhai; Szymon Mazurek; Jakub Caputa; Jan K. Argasinski; Maciej Wielgosz (CoRR, 2024)

How Does Super-Resolution for Satellite Imagery Affect Different Types of Land Cover? Sentinel-2 Case. - Anna Malczewska; Maciej Wielgosz (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024)

Fast Prediction of Job Execution Times in the ALICE Grid Through GPU-Based Inference with Quantization and Sparsity Techniques. - Tomasz Lelek; Szymon Mazurek; Maciej Wielgosz; Bartosz Balis (ICCS (4), 2025)

Modified U-Net with attention gate for enhanced automated brain tumor segmentation. - Shoffan Saifullah; Rafal Drezewski; Anton Yudhana; Maciej Wielgosz; Wahyu Caesarendra (Neural Comput. Appl., 2025)

Three-Factor Learning in Spiking Neural Networks: An Overview of Methods and Trends from a Machine Learning Perspective. - Szymon Mazurek; Jakub Caputa; Jan K. Argasinski; Maciej Wielgosz (CoRR, 2025)

Spatiotemporal Analysis of Forest Machine Operations Using 3D Video Classification. - Maciej Wielgosz; Simon Berg; Heikki Korpunen; Stephan Hoffmann (CoRR, 2025)

ForestFormer3D: A Unified Framework for End-to-End Segmentation of Forest LiDAR 3D Point Clouds. - Binbin Xiang; Maciej Wielgosz; Stefano Puliti; Kamil Král; Martin Krucek; Azim Missarov; Rasmus Astrup (CoRR, 2025)

Analyzing Internal Activity and Robustness of SNNs Across Neuron Parameter Space. - Szymon Mazurek; Jakub Caputa; Maciej Wielgosz (CoRR, 2025)