Progress in Polish Artificial Intelligence Research 4

Stały URI zbioruhttp://hdl.handle.net/11652/4774



CONTENTS
1. 3D Reconstruction of Non-Visible Surfaces of Objects from a Single Depth View – Comparative Study Staszak R., Michałek P., Chudziński J., Kopicki M., Belter D. ........................................................................................ 19
2. Challenges of Crop Classification from Satellite Imagery with Eurocrops Dataset Aszkowski P., Kraft M. ........................................................................................ 25
3. Do We Always Need AI for Image Colorization? Śluzek A. ........................................................................................ 31
4. Fault Diagnosis in a Squirrel-Cage Induction Motor Using Thermal Imaging Piechocki M., Kraft M., Pajchrowski T. ........................................................................................ 37
5. Objective Hybrid Quality Assessment of Binary Images with the Use of Shallow Neural Networks Kopytek M., Okarma K. ........................................................................................ 43
6. One-point Hough Transform with Centred Accumulator Chmielewski L. J., Bator M., Gajowniczek K. ........................................................................................ 49
7. Pedestrian Detection with High-resolution Event Camera Wzorek P., Kryjak T. ........................................................................................ 55
8. Recognition of Shoplifting Activities in CCTV Footage Using the Combined CNN-RNN Model Kirichenko L., Pichugina O., Sydorenko B., Yakovlev S. ........................................................................................ 61
9. Spotting Advertisements from Above: Billboard Detection and Segmentation in UAV Imagery Ptak B., Dominiak J., Kraft M. ........................................................................................ 67
10. Transformers Neural Networks Applications in Different Computer Vision Tasks Brodzicki A., Piekarski M., Kostuch A., Noworolnik F., Aleksandrowicz M., Wójcicka A., Jaworek-Korjakowska J. ........................................................................................ 73
11. Weak Supervision in Enemy Detection Based on Computer Game Output Video Stream Rajtar J., Szajerman D. ........................................................................................ 81
12. A Comparison of Shallow Explainable Artificial Intelligence Methods against Grammatical Evolution Approach Sepioło D., Ligęza A. ........................................................................................ 89
13. Clustering Dilemmas – A Study of the Request of Homogenicity within Clusters Versus Diversity Between Clusters Kłopotek M. A. ........................................................................................ 95
14. Contextual ES-adRNN with Attention Mechanisms for Forecasting Smyl S., Dudek G., Pełka P. ........................................................................................ 101
15. Graph-Supported Preparation of GIS Machine Learning Datasets Ernst S. ........................................................................................ 107
16. Hashtag Similarity Based on Laplacian Eigenvalue Spectrum Starosta B., Kłopotek M. A., Wierzchoń S. T. ........................................................................................ 113
17. Improvement of Attention Mechanism Explainability in Prediction of Chemical Molecules’ Properties Durys B., Tomczyk A. ........................................................................................ 119
18. On Usefulness of Dominance Relation for Selecting Counterfactuals from the Ensemble of Explainers Stępka I., Lango M., Stefanowski J. ........................................................................................ 125
19. Towards Detection of Unknown Polymorphic Patterns Using Prior Knowledge Kucharski P., Ślot K. ........................................................................................ 131
20. AI-driven Ecodriving and ETA Solutions for Truck Transport Lipiński P., Morawski M., Napieralski P., Nowok P., Zawiślak B., Hojdys L., Lazar M., Lazarek P., Zając N., Pizoń S., Jakubiec R., Sienkiewicz J., Gołąbek S., Kabocik M., Fedrizzi S., Kuliga M., Frączkiewicz M., Malarz M., Puchalski J., Danysz E., Grajcarek M. ........................................................................................ 139
21. Analysis of Surface EMG Signals to Control of a Bionic Hand Prototype Pieprzycki A., Król D., Wawryka P., Łachut K., Hamera M., Srebro B. ........................................................................................ 145
22. Brief Overview of Selected Research Directions and Applications of Process Mining in KRaKEn Research Group Kluza K., Zaremba M., Sepioło D., Wiśniewski P., Adrian W. T., Gaudio M. T., Jemioło P., Adrian M., Jobczyk K., Ślażyński M., Stachuta-Terlecka B., Ligęza A. ........................................................................................ 151
23. Carbon Footprint Reduction of a Petrochemical Process Supported by ML and Digital Twin modelling Kulikowski S., Romanowski A., Sierszeń A. ........................................................................................ 157
24. Digital Twin for Training Set Generation for Unexploded Ordnance Classification Ściegienka P., Blachnik M. ........................................................................................ 163
25. Energy Dissipation Anomalies in Buildings Morawski M., Tomczyk A., Idaczyk M. ........................................................................................ 165
26. Identification of Damaged AIS Data Based on Clustering and Multi-Label Classification Szarmach M., Czarnowski I. ........................................................................................ 167
27. Integrating Anomaly Detection for Enhanced Data Protection in Cloud-Based Applications Czerkas K., Drozd M., Duraj A., Lichy K., Lipiński P., Morawski M., Napieralski P., Puchała D., Kwapisz M., Warcholiński A., Karbowańczyk M., Wosiak P. ........................................................................................ 173
28. Learning Non-Differentiable Graphs of Utility AI Świechowski M. ........................................................................................ 181
29. Lessons Learned from a Smart City Project with Citizen Engagement Ernst S., Zaworski K., Sokołowski P., Salwa G. ........................................................................................ 187
30. Machine Learning for Water Leak Detection and Localization in the WaterPrime Project Głomb P., Romaszewski M., Cholewa M., Koral W., Madej A., Skrabski M., Kołodziej K. ........................................................................................ 193
31. Performance Analysis of Machine Learning Platforms Using Cloud Native Technology on Edge Devices Cłapa K., Grudzień K., Sierszeń A. ........................................................................................ 195
32. RNN-based Phase Unwrapping for Enabling Vital Parameter Monitoring with FMCW Radars Łuczak P., Hausman S., Ślot K. ........................................................................................ 201
33. Statistical Method for Photovoltaic Power Forecasting Basing on Signal Components Decomposition Parczyk P., Burduk R. ........................................................................................ 207
34. Text-to-music Models and Their Evaluation Methods Modrzejewski M., Rokita P. ........................................................................................ 213
35. Towards Ontology-Driven Verification of Car Claims Settlement Pancerz K., Wolski J. ........................................................................................ 219
36. Using Security Games against Wild Dumping Sites Adrian M., Markiewicz J. ........................................................................................ 225
37. VideoAI – System for Synchronization of Electronic Program Guides Wasilewski J., Sochaj B., Gaca A. ........................................................................................ 231
38. Identification of Melanocytic Skin Lesions Using Deep Learning Methods Paja W., Szkoła J., Pancerz K., Sarzyński J., Żychowska M. ........................................................................................ 239
39. Loss Function Influence on Uncertainty Estimation for White Matter Lesions 3D Segmentation in a Shifted Domain Setting Kaczmarska M., Majek K. ........................................................................................ 245
40. Multi-task Learning for Classification, Segmentation, Reconstruction, and Detection on Chest CT Scans Hryniewska-Guzik W., Kędzierska M., Biecek P. ........................................................................................ 251
41. Supporting Surgical Training with the Help of Computer Vision and Machine Learning Methods Forczmański P., Ryder Y. C., Mott N. M., Gross C. L., Yu J. B., Rooney D. M., Jeffcoach D. R., Bidwell S., Anidi C., Rosenthal L., Kim G. J. ........................................................................................ 259
42. A Convolutional and Recurrent Neural Network-based Approach for Speech Emotion Recognition Duch P., Wiatrowska I., Kapusta P. ........................................................................................ 267
43. Aaron Earned an Iron Urn: Speech-to-IPA Models Improve Diagnostic of Pronunciation Olejnik F., Stachowiak R., Krysińska I., Morzy M. ........................................................................................ 273
44. Anonymizer for Polish Language Walkowiak T., Gniewkowski M., Pogoda M., Ropiak N. ........................................................................................ 281
45. A Hybrid Fuzzy-Rough Approach to Handling Missing Data in a Fall Detection System Mroczek T., Gil D., Pękala B. ........................................................................................ 285
46. Customer Churn Analytics Using Monotonic Rules Szeląg M., Słowiński R. ........................................................................................ 287
47. Application of Pawlak’s Conflict Model to Generate Coalitions of Local Tables with Similar Values on Conditional Attributes Przybyła-Kasperek M., Kusztal K. ........................................................................................ 293
48. A Novel DNN-based Image Watermarking Algorithm Kovačević S., Pavlović K., Djurović I. ........................................................................................ 301
49. Autoregressive Label-Conditioned Autoencoder for Controllable Image-To-Video Generation Kubicki K., Ślot K. ........................................................................................ 307
50. Building Energy Use Intensity Prediction with Artificial Neural Networks Stokfiszewski K., Sztoch P., Sztoch R., Wosiak A. ........................................................................................ 313
51. Grounded HyperSymbolic Representations Learned through Gradient-Based Optimization Łuczak P., Ślot K., Kucharski J. ........................................................................................ 319
52. Increasing Skin Lesions Classification Rates using Convolutional Neural Networks with Invariant Dataset Augmentation and the Three-Point Checklist of Dermoscopy Milczarski P., Borowski N., Beczkowski M. ........................................................................................ 325
53. A Novel Learning Multi-Swarm Particle Swarm Optimization Borowska B. ........................................................................................ 337
54. Are Quantified Boolean Formulas Hard for Reason-Able Embeddings? Potoniec J. ........................................................................................ 343
55. Dynamic Mutation Control in Continuous Genetic Algorithms Wieczorek Ł., Ignaciuk P. ........................................................................................ 349
56. Local Energy Redistribution Units for Space Dimensionality Reduction in Data Classification Puchała D. ........................................................................................ 355
57. MPTCP Congestion Control Algorithms for Streaming Applications – Performance Evaluation in Public Networks Łuczak Ł. P., Ignaciuk P., Morawski M. ........................................................................................ 361
58. Optimized Mutation Operator in Evolutionary Approach to Stackelberg Security Games Żychowski A., Mańdziuk J. ........................................................................................ 367
59. Simulation of the Quantum Heat Engine in the Quantum Register Ostrowski M. ........................................................................................ 373
60. Socio-cognitive Flock-based Optimization Urbańczyk A., Czech K., Byrski A. ........................................................................................ 381
61. A New Approach to Learning of 3D Characteristic Points for Vehicle Pose Estimation Nowak T., Skrzypczyński P. ........................................................................................ 389
62. A Reinforcement Learning Framework for Motion Planning of Autonomous Vehicles Orłowski M., Skruch P. ........................................................................................ 395
63. BDOT10k-seg: A Dataset for Semantic Segmentation Kos A., Majek K. ........................................................................................ 401
64. Beacon-based Swarm Search and Rescue Ratnayake S., Figat M. ........................................................................................ 407
65. Intelligent Anticipatory Mobile Robot Networks for Autonomous Fruit Harvesting Skulimowski A. M. J., Karimi M. ........................................................................................ 411
66. Evolution of Robotic System Specification Methodology Figat M., Zieliński C. ........................................................................................ 421
67. Improving RGB-D Visual Odometry with Depth Learned from a Better Sensor’s Output Kostusiak A. ........................................................................................ 429
68. Mixing Synthetic and Real-world Datasets Strategy for Improved Generalization of the CNN Młodzikowski K., Belter D. ........................................................................................ 435
69. NeRF-based RGB-D Images Generation in Robotics – Experimental Study Kulecki B., Belter D. ........................................................................................ 443
70. Predictive User Interface for Emerging Experiences Kapusta P. Duch P. ........................................................................................ 449
71. Semantic Segmentation for Autonomous Drone Delivery SUADD’23 Challenge Mrukwa A., Majek K. ........................................................................................ 451
72. Semi-formal Methods for Security Informed Safety Assessment of Robotic Systems Kharchenko V., Abakumov A., Yakovlev S. ........................................................................................ 457
73. Using Publicly Available Building Data to Improve 3D Map Krygiel K., Majek K., Będkowski J. ........................................................................................ 459
74. AloneKnight – Enabling Affective Interaction within Mobile Video Games Jemioło P., Świder K., Storman D., Adrian W. T. ........................................................................................ 467
75. AMUseBot: Towards Making the Most out of a Task-oriented Dialogue System Christop I., Dudzic K., Krzymiński M. ........................................................................................ 473
76. Hierarchical Distributed Cluster-based Method for Robotic Swarms Mastej B., Figat M. ........................................................................................ 479
77. Lung Xray Images Analysis for COVID-19 Diagnosis Kloska A., Tarczewska M., Giełczyk A., Marciniak B. ........................................................................................ 485
78. On Parameters of Migration in PEA Computing Biełaszek S., Byrski A. ........................................................................................ 491
79. On the Importance of the RGB-D Sensor Model in the CNN-based Robotic Perception Zieliński M., Belter D. ........................................................................................ 495
80. On the Selection of a Machine Learning model in TinyML Devices – Preliminary Study Puślecki T., Walkowiak K. ........................................................................................ 501
81. Valuing Passes in Actions Leading to the Third Zone on the Pitch with Machine Learning Methods Tylka M., Wałęsa S., Girejko K., Kaczmarek J., Grzelak B., Piłka T. ........................................................................................ 507

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Autorsearch.filters.applied.operator.equals: search.filters.author.Majek, Karol

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  • Pozycja
    Using Publicly Available Building Data to Improve 3D Map
    (Wydawnictwo Politechniki Łódzkiej, 2023) Krygiel, Krzysztof; Majek, Karol; Będkowski, Janusz
    In this paper, we address the problem of 3D Map accuracy. No access to RTK GPS or LIDAR leads to poor accuracy of the map. High-rise buildings cause even greater trajectory errors. We used artificial intelligence methods to integrate publicly available building data and show that it can improve map accuracy from monocular camera and inaccurate GPS receiver. The main novelty is a method of building elevation detection in sparse point cloud data. We match detected elevations with building data and use modified bundle-adjustment algorithm to improve the map. We show that proposed approach decreases the trajectory error.
  • Pozycja
    Semantic Segmentation for Autonomous Drone Delivery SUADD’23 Challenge
    (Wydawnictwo Politechniki Łódzkiej, 2023) Mrukwa, Anna; Majek, Karol
    The popularity of drones as well as other different flying devices remains undeterred for several years now, with various industries recognizing their usefulness in a range of applications. However, the effectiveness of such systems is heavily dependent on real-time autonomous surface identification. The goal of this work is to evaluate recently published dataset dedicated to Unmanned Aircraft Systems. We performed experiments using several semantic segmentation neural network architectures. We outline possible improvements for future research and promising results for attentionbased solutions in the field.
  • Pozycja
    BDOT10k-seg: A Dataset for Semantic Segmentation
    (Wydawnictwo Politechniki Łódzkiej, 2023) Kos, Aleksandra; Majek, Karol
    In this work, we describe BDOT10k-seg, a novel aerial dataset for semantic and instance segmentation. Our data covers almost the entire territory of Poland (314,000 km2) and provides precise pixel-level annotations for 286 classes of topographical objects, including buildings, roads, rivers, lakes, airports, agricultural areas, and forests. BDOT10-seg consists of 60,718 images with a resolution of 3 to 75 centimeters per pixel, and more than 40 million object instances. The average image size is 12,367 px because, unlike other publicly available datasets, we do not modify the source orthoimages. The code for generating the BDOT10k-seg dataset is publicly available.
  • Pozycja
    Loss Function Influence on Uncertainty Estimation for White Matter Lesions 3D Segmentation in a Shifted Domain Setting
    (Wydawnictwo Politechniki Łódzkiej, 2023) Kaczmarska, Marta; Majek, Karol
    The aim of this study is to address the problem of distributional shift for white matter Multiple Sclerosis lesion segmentation models. The impact of loss function on models performance and uncertainty estimation is evaluated. The evaluation is performed on two in-domain and one out-ofdomain dataset consisting of 3D FLAIR Magnetic Resonance images. Our experiments show that application of segmentation losses (eg. Dice) translate into reduced models robustness and poorer uncertainty estimation compared with classification losses (eg. CE). The source code is publicly available.