%0 Book Section %B Inżynieria Internetu przyszłości część 2 %D 2013 %G eng %I Oficyna Wydawnicza PW %T Aplikacje Sieci Świadomej Treści %@ 978-83-7814-099-3 %& Aplikacje Sieci Świadomej Treści %0 Book Section %B Gesture and Sign Language in Human-Computer Interaction and Embodied Communication %D 2012 %G eng %I Springer Berlin Heidelberg %T Choosing and Modeling the Hand Gesture Database for a Natural User Interface %7 Lecture Notes in Artificial Intelligence %0 Journal Article %B GW 2011: the 9th International Gesture in Embodied Communication and Human-Computer InteractionWorkshop %D 2011 %G eng %T Choosing and modeling hand gesture database for natural user interface %0 Journal Article %B Lecture Notes in Computer Science, Human-Computer Interaction – INTERACT %D 2011 %G eng %T Unsupervised Parameter Selection for Gesture Recognition with Vector Quantization and Hidden Markov Models %V 6949 %0 Journal Article %B Przegląd telekomunikacyjny %D 2012 %G eng %P 1491–1502 %T Aplikacje sieci świadomej treści %0 Generic %D 2011 %G eng %T Towards a natural gesture interface: LDA-based gesture separability %U https://arxiv.org/abs/1109.5034 %0 Journal Article %B Lecture Notes in Artificial Intelligence %D 2014 %G eng %P 757–768 %T Dimensionality reduction of dynamic animations using HO-SVD %V 8467 %0 Journal Article %B arXiv:1310.1240 %D 2013 %G eng %T Compression of animated 3D models using HO-SVD %0 Journal Article %B Journal of Artificial Intelligence and Soft Computing Research %D 2013 %G eng %P 277–289 %T Dimensionality Reduction of Dynamic Mesh Animations Using HO-SVD %V 3 %0 Generic %B Computer Recognition Systems %D 2011 %G eng %I Springer %P 365–373 %T The Effect of Multiple Training Sequences on HMM Classification of Motion Capture Gesture Data %V 4 %8 2011 %0 Journal Article %B Advances in Soft Computing %D 2009 %G eng %P 71–78 %T 3D Mesh Approximation Using Vector Quantization %V 57/2009 %8 V %0 Conference Paper %B Image Processing Theory Tools and Applications (IPTA), 2014 4th International Conference on %D 2014 %G eng %I IEEE %P 404–409 %T Natural hand gestures for human identification in a Human-Computer Interface %8 10 %0 Journal Article %B Theoretical and Applied Informatics %D 2010 %G eng %P 131–140 %T Optimization of a Vector Quantizer's Quality for 3D Mesh Applications %V 22 %8 9 %0 Conference Paper %B Image Processing & Communications Challenges %D 2009 %G eng %I Academy Publishing House EXIT %P 302–308 %T 3D Mesh Identification Using Random Walks and Hidden Markov Models %0 Book Section %B Computer Networks 2011. Communications in Computer and Information Science 160. %D 2011 %G eng %P 459–464 %T Virtual Museum as an Example of 3D Content Distribution in the Architecture of a Future Internet %0 Conference Paper %B Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications %D 2016 %G eng %R 10.5220/0005723501380145 %T Parameter Estimation for HOSVD-based Approximation of Temporally Coherent Mesh Sequences %@ 978-989-758-175-5 %0 Journal Article %B ISPRS Journal of Photogrammetry and Remote Sensing %D 2016 %G eng %P 60 - 76 %R http://dx.doi.org/10.1016/j.isprsjprs.2016.08.011 %T Semi-supervised hyperspectral classification from a small number of training samples using a co-training approach %U http://www.sciencedirect.com/science/article/pii/S0924271616303446 %V 121 %0 Journal Article %B Forensic Science International %D 2018 %G eng %R https://doi.org/10.1016/j.forsciint.2018.06.040 %T Application of hyperspectral imaging and Machine Learning methods for the detection of gunshot residue patterns %U http://www.sciencedirect.com/science/article/pii/S0379073818303657 %V 290 %8 07/2018 %& 227 %0 Conference Paper %B Computer and Information Sciences %D 2018 %G eng %I Springer International Publishing %T Adaptive, Hubness-Aware Nearest Neighbour Classifier with Application to Hyperspectral Data %@ 978-3-030-00840-6 %0 Conference Paper %B Computer and Information Sciences %C Cham %D 2018 %G eng %I Springer International Publishing %T Matrix and Tensor-Based Approximation of 3D Face Animations from Low-Cost Range Sensors %@ 978-3-030-00840-6 %0 Journal Article %B IEEE Geoscience and Remote Sensing Letters %D 2019 %G eng %P 467-471 %R 10.1109/LGRS.2018.2868862 %T A Spatial-Spectral Disagreement-Based Sample Selection With an Application to Hyperspectral Data Classification %V 16 %8 March %0 Generic %B PP-RAI'2019 %C Wrocław, Poland %D 2019 %G eng %I Wroclaw University of Science and Technology %P p. 121 %T Band selection with Higher Order Multivariate Cumulants for small target detection in hyperspectral images %U https://arxiv.org/abs/1808.03513 %8 2019 %@ 978-83-943803-2-8 %0 Generic %B PP-RAI'2019 %C Wrocław, Poland %D 2019 %G eng %I Wroclaw University of Science and Technology %T Unsupervised deep learning approach to hyperspectral anomaly detection %@ 978-83-943803-2-8 %0 Book Section %B Hyperspectral Remote Sensing: Theory & Applications %D 2020 %G eng %I Elsevier %T Anomaly detection in hyperspectral remote sensing images %U https://www.elsevier.com/books/hyperspectral-remote-sensing/pandey/978-0-08-102894-0 %@ 978-0-08-102894-0 %0 Journal Article %B Sensors %D 2020 %G eng %N Recent Advances in Multi- and Hyperspectral Image Analysis %R https://doi.org/10.3390/s20226666 %T Blood Stain Classification with Hyperspectral Imaging and Deep Neural Networks %U https://www.mdpi.com/1424-8220/20/22/6666 %V 20 %8 11/2020 %0 Journal Article %B Animals %D 2020 %G eng %N 12 %P 2201 %T Comparison of the Surface Thermal Patterns of Horses and Donkeys in Infrared Thermography Images %V 10 %8 11/2020 %0 Generic %D 2020 %G eng %R 10.5281/zenodo.3984905 %T A Dataset for Evaluating Blood Detection in Hyperspectral Images [Data set] %U https://doi.org/10.5281/zenodo.3984905 %0 Journal Article %B Forensic Science International %D 2021 %G eng %R https://doi.org/10.1016/j.forsciint.2021.110701 %T A dataset for evaluating blood detection in hyperspectral images %U https://arxiv.org/abs/2008.10254 %V 320 %0 Generic %D 2020 %G eng %R http://doi.org/10.5281/zenodo.4085075 %T Comparison of surface thermal patterns of horses and donkeys in IRT images [Data set] %U https://zenodo.org/record/4085075 %0 Journal Article %B Sensors %D 2021 %G eng %R 10.3390/s21072293 %T Hyperspectral Classification of Blood-Like Substances Using Machine Learning Methods Combined with Genetic Algorithms in Transductive and Inductive Scenarios %U https://www.mdpi.com/1424-8220/21/7/2293 %V 21 %8 03/2021 %0 Generic %B 21st International Conference on Image Analysis and Processing %C Lecce, Italy %D 2022 %G eng %I Springer, Cham %R 10.1007/978-3-031-06427-2_33 %T Improving Autoencoder Training Performance for Hyperspectral Unmixing with Network Reinitialisation %U https://arxiv.org/abs/2109.13748 %V 13231 %8 05/2022 %0 Journal Article %B Water Supply %D 2023 %G eng %N 6 %R 10.2166/ws.2023.118 %T Detection of emergent leaks using machine learning approaches %U https://doi.org/10.2166/ws.2023.118 %V 23 %8 05/2023 %& 2370 %0 Journal Article %B medXriv %D 2023 %G eng %R 10.1101/2023.08.04.23293640 %T The analysis of heart rate variability and accelerometer mobility data in the assessment of symptom severity in psychotic disorder patients using a wearable Polar H10 sensor %U https://www.medrxiv.org/content/10.1101/2023.08.04.23293640v1 %8 08/2023 %0 Generic %D 2023 %G eng %R 10.5281/zenodo.8171266 %T HRV-ACC: a dataset with R-R intervals and accelerometer data for the diagnosis of psychotic disorders using a Polar H10 wearable sensor %U https://zenodo.org/record/8171266 %0 Journal Article %B Particle & Particle Systems Characterization %D 2023 %G eng %R https://doi.org/10.1002/ppsc.202200204 %T Hyperspectral Imaging as a Facile and Non-Destructive Method for Size Analysis of Gold Nanoparticles Deposited on Porous Materials %0 Conference Paper %B Wojciechowski A.(Ed.), Lipiński P.(Ed.)., Progress in Polish Artificial Intelligence Research 4, Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928. %D 2023 %G eng %I Wydawnictwo Politechniki Łódzkiej %T Machine Learning for Water Leak Detection and Localization in the WaterPrime Project %0 Journal Article %B Computers in Biology and Medicine %D 2024 %G eng %R https://doi.org/10.1016/j.compbiomed.2024.108544 %T Assessment of symptom severity in psychotic disorder patients based on heart rate variability and accelerometer mobility data %U https://www.sciencedirect.com/science/article/pii/S0010482524006280 %V 176 %8 05/2024 %0 Journal Article %B arXiv preprint arXiv:2406.04926 %D 2024 %G eng %T Through the Thicket: A Study of Number-Oriented LLMs derived from Random Forest Models %U https://arxiv.org/abs/2406.04926 %8 06/2024 %0 Journal Article %B IEEE Sensors Journal %D 2024 %G eng %R 10.1109/JSEN.2024.3413889 %T ‘Just One More Sensor is Enough’ – Iterative Water Leak Localization with Physical Simulation and a Small Number of Pressure Sensors %8 06/2024 %0 Journal Article %B arXiv preprint arXiv:2410.02772 %D 2024 %G eng %R https://doi.org/10.48550/arXiv.2410.02772 %T Efficient Numerical Calibration of Water Delivery Network Using Short-Burst Hydrant Trials %U https://arxiv.org/abs/2410.02772 %8 09/2024 %0 Generic %B 5th Polish Conference on Artificial Intelligence (PP-RAI 2024) %D 2024 %G eng %T Calibration of Water Demand Network Through a Machine Learned Digital Twin Model %0 Generic %B 5th Polish Conference on Artificial Intelligence (PP-RAI 2024) %C Warsaw, Poland %D 2024 %G eng %T Poster: Explainable classification of multimodal time series using LLMs %8 04/2024 %0 Journal Article %B Journal of Artificial Intelligence and Soft Computing Research %D 2025 %G eng %N 3 %R https://doi.org/10.2478/jaiscr-2025-0014 %T Through the Thicket: A Study of Number-Oriented LLMS Derived from Random Forest Models %V 15 %8 03/2025 %& 279 %0 Conference Paper %B International Conference on Computational Science 2025 %D 2025 %G eng %R 10.48550/arXiv.2502.21055 %T Quantum-aware Transformer model for state classification %U https://link.springer.com/chapter/10.1007/978-3-031-97570-7_15 %0 Journal Article %B arXiv preprint %G eng %R https://doi.org/10.48550/arXiv.2504.09956 %T Semantic Depth Matters: Explaining Errors of Deep Vision Networks through Perceived Class Similarities %U arXiv:2504.09956 %0 Journal Article %B Bulletin of the Polish Academy of Sciences Technical Sciences %D 2025 %G eng %N 5 %R 10.24425/bpasts.2025.154279 %T Potential of quantum machine learning for processing multispectral Earth observation data %U https://journals.pan.pl/dlibra/publication/154279/edition/135180/content %V 73 %8 08/2025 %0 Journal Article %B PLOS Computational Biology %D 2025 %G eng %R 10.1371/journal.pcbi.1012983 %T Deep learning approach for automatic assessment of schizophrenia and bipolar disorder in patients using R-R intervals %V 21 %8 09/2025 %& 1 %0 Journal Article %B Bulletin of the Polish Academy of Sciences Technical Sciences %D 2025 %G eng %R DOI: 10.24425/bpasts.2025.155891 %T Data structure better than labels? 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Unsupervised heuristics for SVM hyperparameter estimation %0 Journal Article %B Journal of Water Resources Planning and Management - ASCE %D 2026 %G eng %N 4 %R 10.1061/JWRMD5.WRENG-6839 %T Efficient Numerical Calibration of Water Delivery Network Using Short-Burst Hydrant Trials %U https://doi.org/10.1061/JWRMD5.WRENG-6839 %V 152 %8 02/2026 %0 Generic %B 6th Polish Conference on Artificial Intelligence (PP-RAI 2025) %D 2025 %G eng %T Towards AI-assisted Science with PLAI4SCIENCE - new Polish Research Infrastructure %8 04/2025 %0 Journal Article %B Geoscience and Remote Sensing Letters %D 2026 %G eng %T Map-Guided Cross-Training for Building Detection %0 Journal Article %B IEEE Internet of Things Journal %D 2026 %T Enabling Cloud-Level Accuracy in Edge AI through IoT Data Preprocessing %0 Journal Article %B arXiv preprint arXiv %D 2026 %R 10.48550/ARXIV.2606.22496 %T Enabling Cloud-Level Accuracy in Edge AI through IoT Data Preprocessing %U https://arxiv.org/abs/2606.22496 %0 Generic %D 2026 %R 10.5281/ZENODO.20783874 %T AIRWISE: Environmental Sensor and LLM Query Dataset for Edge AI-Based Air-Quality and Thermal-Comfort Analytics %U https://zenodo.org/doi/10.5281/zenodo.20783874 %0 Generic %D 2026 %R 10.1109/JSTARS.2026.3742586 %T Toward Seasonal Guidelines for Robust Deep-Learning Sentinel-2 Building Detection in Different Area Types