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ORCIDJakub Nalepa
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- affiliation: Silesian University of Technology, Gliwice, Poland
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2020 – today
- 2024
[j37]Tomasz Jastrzab, Michal Myller, Lukasz Tulczyjew, Miroslaw Blocho, Michal Kawulok, Adam Czornik, Jakub Nalepa:
Standardized validation of vehicle routing algorithms. Appl. Intell. 54(2): 1335-1364 (2024)- [j36]Daniel Marek, Jakub Nalepa
:
End-to-end deep learning pipeline for on-board extraterrestrial rock segmentation. Eng. Appl. Artif. Intell. 127(Part B): 107311 (2024) - [c113]Martyna Kurbiel, Agata M. Wijata, Jakub Nalepa:
Predicting the MGMT Promoter Methylation Status in T2-FLAIR Magnetic Resonance Imaging Scans Using Machine Learning. ICPRAM 2024: 872-879 - [i26]Mariusz Bujny, Katarzyna Jesionek, Jakub Nalepa, Karol Miszalski-Jamka, Katarzyna Widawka-Zak, Sabina Wolny, Marcin Kostur:
Coronary artery segmentation in non-contrast calcium scoring CT images using deep learning. CoRR abs/2403.02544 (2024) - [i25]Vladimir Zaigrajew, Hubert Baniecki, Lukasz Tulczyjew, Agata M. Wijata, Jakub Nalepa, Nicolas Longépé, Przemyslaw Biecek:
Red Teaming Models for Hyperspectral Image Analysis Using Explainable AI. CoRR abs/2403.08017 (2024) - 2023
- [j35]Krzysztof Kotowski, Damian Kucharski, Bartosz Machura, Szymon Adamski, Benjamín Gutiérrez-Becker, Agata Krason, Lukasz Zarudzki, Jean Tessier, Jakub Nalepa:
Detecting liver cirrhosis in computed tomography scans using clinically-inspired and radiomic features. Comput. Biol. Medicine 152: 106378 (2023) - [j34]Jakub Nalepa, Krzysztof Kotowski, Bartosz Machura, Szymon Adamski, Oskar Bozek, Bartosz Eksner, Bartosz Kokoszka, Tomasz Pekala, Mateusz Radom, Marek Strzelczak, Lukasz Zarudzki, Agata Krason, Filippo Arcadu, Jean Tessier:
Deep learning automates bidimensional and volumetric tumor burden measurement from MRI in pre- and post-operative glioblastoma patients. Comput. Biol. Medicine 154: 106603 (2023) - [j33]Bogdan Ruszczak, Krzysztof Kotowski, Jacek Andrzejewski, Christoph Haskamp, Jakub Nalepa:
OXI: An online tool for visualization and annotation of satellite time series data. SoftwareX 23: 101476 (2023) - [j32]Artur Miroszewski, Jakub Mielczarek, Grzegorz Czelusta, Filip Szczepanek, Bartosz Grabowski, Bertrand Le Saux, Jakub Nalepa:
Detecting Clouds in Multispectral Satellite Images Using Quantum-Kernel Support Vector Machines. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 16: 7601-7613 (2023) - [j31]Tomasz Tarasiewicz, Jakub Nalepa, Reuben A. Farrugia, Gianluca Valentino, Mang Chen, Johann A. Briffa, Michal Kawulok:
Multitemporal and Multispectral Data Fusion for Super-Resolution of Sentinel-2 Images. IEEE Trans. Geosci. Remote. Sens. 61: 1-19 (2023) - [c112]Miroslaw Blocho, Tomasz Jastrzab, Jakub Nalepa:
Parallel Cooperative Memetic Co-evolution for VRPTW. GECCO Companion 2023: 53-54 - [c111]Jakub Sadel, Michal Kawulok, Mateusz Przeliorz, Jakub Nalepa, Daniel Kostrzewa:
Genetic Structural NAS: A Neural Network Architecture Search with Flexible Slot Connections. GECCO Companion 2023: 79-80 - [c110]Rafal Dubel, Agata M. Wijata, Jakub Nalepa:
On the Impact of Noisy Labels on Supervised Classification Models. ICCS (2) 2023: 111-119 - [c109]Bogdan Ruszczak, Agata M. Wijata, Jakub Nalepa:
Estimating Chlorophyll Content from Hyperspectral Data Using Gradient Features. ICCS (2) 2023: 196-203 - [c108]Bogdan Ruszczak, Krzysztof Kotowski, Jacek Andrzejewski, Alicja Musial, David Evans, Vladimir Zelenevskiy, Sam Bammens, Rodrigo Laurinovics, Jakub Nalepa:
Machine Learning Detects Anomalies in OPS-SAT Telemetry. ICCS (1) 2023: 295-306 - [c107]Jaroslaw Goslinski, Filip Malawski, Mariusz Bujny, Marcin Kostur, Karol Miszalski-Jamka, Jakub Nalepa:
Deep Learning Meets Particle Swarm Optimization For Aortic Valve Calcium Scoring From Cardiac Computed Tomography. ICIP 2023: 3469-3473 - [c106]Agata M. Wijata, Jakub Nalepa:
Machine Learning Detects a Biopsy Needle in Ultrasound Images. ICIP 2023: 3548-3552 - [c105]Artur Miroszewski, Jakub Mielczarek, Filip Szczepanek, Grzegorz Czelusta, Bartosz Grabowski, Bertrand Le Saux, Jakub Nalepa:
Optimizing Kernel-Target Alignment for Cloud Detection in Multispectral Satellite Images. IGARSS 2023: 792-795 - [c104]Artur Miroszewski, Jakub Mielczarek, Filip Szczepanek, Grzegorz Czelusta, Bartosz Grabowski, Bertrand Le Saux, Jakub Nalepa:
Cloud Detection in Multispectral Satellite Images Using Support Vector Machines with Quantum Kernels. IGARSS 2023: 796-799 - [c103]Michal Kawulok, Pawel Kowaleczko, Maciej Ziaja, Jakub Nalepa, Daniel Kostrzewa, Daniele Latini, Davide De Santis, Giorgia Salvucci, Ilaria Petracca, Valeria La Pegna, Zoltan Bartalis, Fabio Del Frate:
Understanding the Value of Hyperspectral Image Super-Resolution from Prisma Data. IGARSS 2023: 1489-1492 - [c102]Maciej Ziaja, Pawel Kowaleczko, Jakub Nalepa, Daniel Kostrzewa, Daniele Latini, Davide De Santis, Giorgia Salvucci, Ilaria Petracca, Valeria La Pegna, Fabio Del Frate, Michal Kawulok:
Hyperspectral Image Pansharpening: The Prisma Case Study. IGARSS 2023: 1633-1636 - [c101]Piotr Bosowski, Nicolas Longépé, Bertrand Le Saux, Jakub Nalepa:
Knowledge Distillation for Memory-Efficient On-Board Image Classification of Mars Imagery. IGARSS 2023: 2018-2021 - [c100]Michal Gumiela, Alicja Musial, Agata M. Wijata, Dawid Lazaj, Jonas Weiss, Patricia Sagmeister, Thomas Morf, Martin L. Schmatz, Jakub Nalepa:
Benchmarking Space-Based Data Center Architectures. IGARSS 2023: 4970-4973 - [c99]Agata M. Wijata, Michel-François Foulon, Yves Bobichon, Nicolas Longépé, Roberto Camarero, Raffaele Vitulli, Marco Celesti, Gianluigi Di Cosimo, Ferran Gascon, Jens Nieke, Jakub Nalepa:
Toward On-Board Methane Detection in Hyperspectral Images. IGARSS 2023: 5866-5869 - [c98]Lukasz Tulczyjew, Michal Kawulok, Nicolas Longépé, Bertrand Le Saux, Jakub Nalepa:
Unbiased Validation of Hyperspectral Unmixing Algorithms. IGARSS 2023: 7344-7347 - [i24]Tomasz Tarasiewicz, Jakub Nalepa, Reuben A. Farrugia, Gianluca Valentino, Mang Chen, Johann A. Briffa, Michal Kawulok:
Multitemporal and multispectral data fusion for super-resolution of Sentinel-2 images. CoRR abs/2301.11154 (2023) - [i23]Artur Miroszewski, Jakub Mielczarek, Grzegorz Czelusta, Filip Szczepanek, Bartosz Grabowski, Bertrand Le Saux, Jakub Nalepa:
Detecting Clouds in Multispectral Satellite Images Using Quantum-Kernel Support Vector Machines. CoRR abs/2302.08270 (2023) - [i22]Maria Ferlin, Sylwia Majchrowska, Marta A. Plantykow, Alicja Kwasniwska, Agnieszka Mikolajczyk-Barela, Milena Olech, Jakub Nalepa:
On the Importance of Sign Labeling: The Hamburg Sign Language Notation System Case Study. CoRR abs/2302.10768 (2023) - [i21]Bartosz Grabowski, Maciej Ziaja, Michal Kawulok, Piotr Bosowski, Nicolas Longépé, Bertrand Le Saux, Jakub Nalepa:
Squeezing nnU-Nets with Knowledge Distillation for On-Board Cloud Detection. CoRR abs/2306.09886 (2023) - [i20]Artur Miroszewski, Jakub Mielczarek, Filip Szczepanek, Grzegorz Czelusta, Bartosz Grabowski, Bertrand Le Saux, Jakub Nalepa:
Optimizing Kernel-Target Alignment for cloud detection in multispectral satellite images. CoRR abs/2306.14515 (2023) - [i19]Artur Miroszewski, Jakub Mielczarek, Filip Szczepanek, Grzegorz Czelusta, Bartosz Grabowski, Bertrand Le Saux, Jakub Nalepa:
Cloud Detection in Multispectral Satellite Images Using Support Vector Machines With Quantum Kernels. CoRR abs/2307.07281 (2023) - [i18]Artur Miroszewski, Jakub Nalepa, Bertrand Le Saux, Jakub Mielczarek:
Quantum Machine Learning for Remote Sensing: Exploring potential and challenges. CoRR abs/2311.07626 (2023) - 2022
- [j30]Jakub Nalepa, Szymon Adamski, Krzysztof Kotowski, Sylwia Chelstowska, Magdalena Machnikowska-Sokolowska, Oskar Bozek, Agata Wisz, Elzbieta Jurkiewicz:
Segmenting pediatric optic pathway gliomas from MRI using deep learning. Comput. Biol. Medicine 142: 105237 (2022) - [j29]Lukasz Tulczyjew, Michal Kawulok, Nicolas Longépé, Bertrand Le Saux, Jakub Nalepa:
Graph Neural Networks Extract High-Resolution Cultivated Land Maps From Sentinel-2 Image Series. IEEE Geosci. Remote. Sens. Lett. 19: 1-5 (2022) - [j28]Lukasz Tulczyjew, Michal Kawulok, Nicolas Longépé, Bertrand Le Saux, Jakub Nalepa:
A Multibranch Convolutional Neural Network for Hyperspectral Unmixing. IEEE Geosci. Remote. Sens. Lett. 19: 1-5 (2022) - [j27]Bogdan Ruszczak, Agata M. Wijata, Jakub Nalepa:
Unbiasing the Estimation of Chlorophyll from Hyperspectral Images: A Benchmark Dataset, Validation Procedure and Baseline Results. Remote. Sens. 14(21): 5526 (2022) - [j26]Tomasz Gandor, Jakub Nalepa:
First Gradually, Then Suddenly: Understanding the Impact of Image Compression on Object Detection Using Deep Learning. Sensors 22(3): 1104 (2022) - [c97]Jakub Nalepa, Piotr Bosowski, Wojciech Dudzik, Michal Kawulok:
Fusing Deep Learning with Support Vector Machines to Detect COVID-19 in X-Ray Images. ACIIDS (Companion) 2022: 340-353 - [c96]Krzysztof Kotowski, Bartosz Machura, Jakub Nalepa:
Robustifying Automatic Assessment of Brain Tumor Progression from MRI. BrainLes@MICCAI 2022: 90-101 - [c95]Krzysztof Kotowski, Szymon Adamski, Bartosz Machura, Lukasz Zarudzki, Jakub Nalepa:
Infusing Domain Knowledge into nnU-Nets for Segmenting Brain Tumors in MRI. BrainLes@MICCAI 2022: 186-194 - [c94]Krzysztof Kotowski, Szymon Adamski, Bartosz Machura, Wojciech Malara, Lukasz Zarudzki, Jakub Nalepa:
Federated Evaluation of nnU-Nets Enhanced with Domain Knowledge for Brain Tumor Segmentation. BrainLes@MICCAI (2) 2022: 218-227 - [c93]Jakub Nalepa, Stanislaw Czembor, Wojciech Dudzik, Michal Kawulok:
Evolutionary algorithms meet classical and deep machine learning for skin detection in color images. GECCO Companion 2022: 67-68 - [c92]Miroslaw Blocho, Tomasz Jastrzab, Jakub Nalepa:
Cooperative co-evolutionary memetic algorithm for pickup and delivery problem with time windows. GECCO Companion 2022: 176-179 - [c91]Wojciech Dudzik, Jakub Nalepa, Michal Kawulok:
Cascades of evolutionary support vector machines. GECCO Companion 2022: 240-243 - [c90]Tomasz Jastrzab, Michal Myller, Lukasz Tulczyjew, Miroslaw Blocho, Wojciech Ryczko, Michal Kawulok, Jakub Nalepa:
Particle Swarm Optimization Configures the Route Minimization Algorithm. ICCS (1) 2022: 80-87 - [c89]Wojciech Ponikiewski, Jakub Nalepa:
Deep Learning Meets Radiomics For End-To-End Brain Tumor MRI Analysis. ICIP 2022: 1301-1305 - [c88]Agata M. Wijata, Jakub Nalepa:
Unbiased Validation of the Algorithms for Automatic Needle Localization in Ultrasound-Guided Breast Biopsies. ICIP 2022: 3571-3575 - [c87]Jakub Nalepa, Bertrand Le Saux, Nicolas Longépé, Lukasz Tulczyjew, Michal Myller, Michal Kawulok, Krzysztof Smykala, Michal Gumiela:
The Hyperview Challenge: Estimating Soil Parameters from Hyperspectral Images. ICIP 2022: 4268-4272 - [c86]Maciej Ziaja, Jakub Nalepa, Michal Kawulok:
Data Augmentation for Multi-Image Super-Resolution. IGARSS 2022: 119-122 - [c85]Tomasz Tarasiewicz, Lukasz Tulczyjew, Michal Myller, Michal Kawulok, Nicolas Longépé, Jakub Nalepa:
Extracting High-Resolution Cultivated Land Maps from Sentinel-2 Image Series. IGARSS 2022: 175-178 - [c84]Bartosz Grabowski, Maciej Ziaja, Michal Kawulok, Marcin Cwiek, Tomasz Lakota, Nicolas Longépé, Jakub Nalepa:
Are Cloud Detection U-Nets Robust Against in-Orbit Image Acquisition Conditions? IGARSS 2022: 239-242 - [c83]Tomasz Tarasiewicz, Jakub Nalepa, Michal Kawulok:
Semi-Simulated Training Data for Multi-Image Super-Resolution. IGARSS 2022: 481-484 - [c82]Filip Malawski, Jaroslaw Goslinski, Mikolaj Stryja, Katarzyna Jesionek, Marcin Kostur, Karol Miszalski-Jamka, Jakub Nalepa:
Deep Learning Meets Computational Fluid Dynamics to Assess CAD in CCTA. AMAI@MICCAI 2022: 8-17 - [i17]Lukasz Tulczyjew, Michal Kawulok, Nicolas Longépé, Bertrand Le Saux, Jakub Nalepa:
Graph Neural Networks Extract High-Resolution Cultivated Land Maps from Sentinel-2 Image Series. CoRR abs/2208.02349 (2022) - [i16]Lukasz Tulczyjew, Michal Kawulok, Nicolas Longépé, Bertrand Le Saux, Jakub Nalepa:
A Multibranch Convolutional Neural Network for Hyperspectral Unmixing. CoRR abs/2208.02361 (2022) - [i15]Jakub Nalepa, Krzysztof Kotowski, Bartosz Machura, Szymon Adamski, Oskar Bozek, Bartosz Eksner, Bartosz Kokoszka, Tomasz Pekala, Mateusz Radom, Marek Strzelczak, Lukasz Zarudzki, Agata Krason, Filippo Arcadu, Jean Tessier:
Deep learning automates bidimensional and volumetric tumor burden measurement from MRI in pre- and post-operative glioblastoma patients. CoRR abs/2209.01402 (2022) - [i14]Pawel Kowaleczko, Tomasz Tarasiewicz, Maciej Ziaja, Daniel Kostrzewa, Jakub Nalepa, Przemyslaw Rokita, Michal Kawulok:
MuS2: A Benchmark for Sentinel-2 Multi-Image Super-Resolution. CoRR abs/2210.02745 (2022) - [i13]Bartosz Grabowski, Maciej Ziaja, Michal Kawulok, Nicolas Longépé, Bertrand Le Saux, Jakub Nalepa:
Self-Configuring nnU-Nets Detect Clouds in Satellite Images. CoRR abs/2210.13659 (2022) - 2021
- [j25]Wojciech Dudzik, Jakub Nalepa, Michal Kawulok:
Evolving data-adaptive support vector machines for binary classification. Knowl. Based Syst. 227: 107221 (2021) - [j24]Lukasz Tulczyjew, Michal Kawulok, Jakub Nalepa:
Unsupervised Feature Learning Using Recurrent Neural Nets for Segmenting Hyperspectral Images. IEEE Geosci. Remote. Sens. Lett. 18(12): 2142-2146 (2021) - [j23]Jakub Nalepa, Michal Myller, Marcin Cwiek, Lukasz Zak, Tomasz Lakota, Lukasz Tulczyjew, Michal Kawulok:
Towards On-Board Hyperspectral Satellite Image Segmentation: Understanding Robustness of Deep Learning through Simulating Acquisition Conditions. Remote. Sens. 13(8): 1532 (2021) - [j22]Maciej Ziaja, Piotr Bosowski, Michal Myller, Grzegorz Gajoch, Michal Gumiela, Jennifer Protich, Katherine Borda, Dhivya Jayaraman, Renata Dividino, Jakub Nalepa:
Benchmarking Deep Learning for On-Board Space Applications. Remote. Sens. 13(19): 3981 (2021) - [j21]Jakub Nalepa, Michal Myller, Lukasz Tulczyjew, Michal Kawulok:
Deep Ensembles for Hyperspectral Image Data Classification and Unmixing. Remote. Sens. 13(20): 4133 (2021) - [j20]Jakub Nalepa:
Recent Advances in Multi- and Hyperspectral Image Analysis. Sensors 21(18): 6002 (2021) - [c81]Krzysztof Kotowski, Szymon Adamski, Bartosz Machura, Lukasz Zarudzki, Jakub Nalepa:
Coupling nnU-Nets with Expert Knowledge for Accurate Brain Tumor Segmentation from MRI. BrainLes@MICCAI (2) 2021: 197-209 - [c80]Pawel Benecki, Szymon Piechaczek, Daniel Kostrzewa, Jakub Nalepa:
Detecting anomalies in spacecraft telemetry using evolutionary thresholding and LSTMs. GECCO Companion 2021: 143-144 - [c79]Tomasz Tarasiewicz, Jakub Nalepa, Michal Kawulok:
A Graph Neural Network For Multiple-Image Super-Resolution. ICIP 2021: 1824-1828 - [c78]Piotr Bosowski, Joanna Bosowska, Jakub Nalepa:
Evolving Deep Ensembles For Detecting Covid-19 In Chest X-Rays. ICIP 2021: 3772-3776 - [c77]Lukasz Tulczyjew, Jakub Nalepa:
Investigating the Impact of the Training Set Size on Deep Learning-Powered Hyperspectral Unmixing. IGARSS 2021: 2024-2027 - [c76]Michal Kawulok, Tomasz Tarasiewicz, Jakub Nalepa, Diana Tyrna, Daniel Kostrzewa:
Deep Learning for Multiple-Image Super-Resolution of Sentinel-2 Data. IGARSS 2021: 3885-3888 - [c75]Bartosz Grabowski, Maciej Ziaja, Michal Kawulok, Jakub Nalepa:
Towards Robust Cloud Detection in Satellite Images Using U-Nets. IGARSS 2021: 4099-4102 - 2020
- [j19]Pablo Ribalta Lorenzo, Lukasz Tulczyjew, Michal Marcinkiewicz, Jakub Nalepa:
Hyperspectral Band Selection Using Attention-Based Convolutional Neural Networks. IEEE Access 8: 42384-42403 (2020) - [j18]Jakub Nalepa, Pablo Ribalta Lorenzo, Michal Marcinkiewicz, Barbara Bobek-Billewicz, Pawel Wawrzyniak, Maksym Walczak, Michal Kawulok, Wojciech Dudzik, Krzysztof Kotowski, Izabela Burda, Bartosz Machura, Grzegorz Mrukwa, Pawel Ulrych, Michael P. Hayball:
Fully-automated deep learning-powered system for DCE-MRI analysis of brain tumors. Artif. Intell. Medicine 102: 101769 (2020) - [j17]Jakub Nalepa, Michal Myller, Michal Kawulok:
Training- and Test-Time Data Augmentation for Hyperspectral Image Segmentation. IEEE Geosci. Remote. Sens. Lett. 17(2): 292-296 (2020) - [j16]Michal Kawulok, Pawel Benecki, Szymon Piechaczek, Krzysztof Hrynczenko, Daniel Kostrzewa, Jakub Nalepa:
Deep Learning for Multiple-Image Super-Resolution. IEEE Geosci. Remote. Sens. Lett. 17(6): 1062-1066 (2020) - [j15]Jakub Nalepa, Michal Myller, Michal Kawulok:
Transfer Learning for Segmenting Dimensionally Reduced Hyperspectral Images. IEEE Geosci. Remote. Sens. Lett. 17(7): 1228-1232 (2020) - [j14]Jakub Nalepa, Michal Myller, Yasuteru Imai, Ken-ichi Honda, Tomomi Takeda, Marek Antoniak:
Unsupervised Segmentation of Hyperspectral Images Using 3-D Convolutional Autoencoders. IEEE Geosci. Remote. Sens. Lett. 17(11): 1948-1952 (2020) - [j13]Jakub Nalepa, Marek Antoniak, Michal Myller, Pablo Ribalta Lorenzo, Michal Marcinkiewicz:
Towards resource-frugal deep convolutional neural networks for hyperspectral image segmentation. Microprocess. Microsystems 73: 102994 (2020) - [c74]Tomasz Tarasiewicz, Michal Kawulok, Jakub Nalepa:
Lightweight U-Nets for Brain Tumor Segmentation. BrainLes@MICCAI (2) 2020: 3-14 - [c73]Krzysztof Kotowski, Szymon Adamski, Wojciech Malara, Bartosz Machura, Lukasz Zarudzki, Jakub Nalepa:
Segmenting Brain Tumors from MRI Using Cascaded 3D U-Nets. BrainLes@MICCAI (2) 2020: 265-277 - [c72]Tomasz Tarasiewicz, Jakub Nalepa, Michal Kawulok:
Skinny: A Lightweight U-Net For Skin Detection And Segmentation. ICIP 2020: 2386-2390 - [c71]Jakub Nalepa, Wojciech Dudzik, Michal Kawulok:
Memetic Evolution of Training Sets with Adaptive Radial Basis Kernels for Support Vector Machines. ICPR 2020: 5503-5510 - [c70]Michal Kawulok, Pawel Benecki, Jakub Nalepa, Daniel Kostrzewa:
Evaluating Super-Resolution of Satellite Images: A Proba-V Case Study. IGARSS 2020: 641-644 - [c69]Jakub Nalepa, Lukasz Tulczyjew, Michal Myller, Michal Kawulok:
Hyperspectral Image Classification Using Spectral-Spatial Convolutional Neural Networks. IGARSS 2020: 866-869 - [c68]Jakub Nalepa, Marek Stanek:
Segmenting Hyperspectral Images Using Spectral Convolutional Neural Networks in the Presence of Noise. IGARSS 2020: 870-873 - [c67]Michal Myller, Michal Kawulok, Jakub Nalepa:
Selecting Features from Time Series Using Attention-Based Recurrent Neural Networks. S+SSPR 2020: 87-97 - [c66]Jakub Nalepa, Krzysztof Hrynczenko, Michal Kawulok:
Multiple-Image Super-Resolution Using Deep Learning and Statistical Features. S+SSPR 2020: 261-271
2010 – 2019
- 2019
- [j12]Jakub Nalepa, Michal Kawulok:
Selecting training sets for support vector machines: a review. Artif. Intell. Rev. 52(2): 857-900 (2019) - [j11]Pablo Ribalta Lorenzo, Jakub Nalepa, Barbara Bobek-Billewicz, Pawel Wawrzyniak, Grzegorz Mrukwa, Michal Kawulok, Pawel Ulrych, Michael P. Hayball:
Segmenting brain tumors from FLAIR MRI using fully convolutional neural networks. Comput. Methods Programs Biomed. 176: 135-148 (2019) - [j10]Jakub Nalepa, Michal Marcinkiewicz, Michal Kawulok:
Data Augmentation for Brain-Tumor Segmentation: A Review. Frontiers Comput. Neurosci. 13: 83 (2019) - [j9]Jakub Nalepa, Michal Myller, Michal Kawulok:
Validating Hyperspectral Image Segmentation. IEEE Geosci. Remote. Sens. Lett. 16(8): 1264-1268 (2019) - [c65]Daniel Kostrzewa, Szymon Piechaczek, Krzysztof Hrynczenko, Pawel Benecki, Jakub Nalepa, Michal Kawulok:
Super-Resolution Reconstruction Using Deep Learning: Should We Go Deeper? BDAS 2019: 204-216 - [c64]Pablo Ribalta Lorenzo, Michal Marcinkiewicz, Jakub Nalepa:
Multi-modal U-Nets with Boundary Loss and Pre-training for Brain Tumor Segmentation. BrainLes@MICCAI (2) 2019: 135-147 - [c63]Krzysztof Kotowski, Jakub Nalepa, Wojciech Dudzik:
Detection and Segmentation of Brain Tumors from MRI Using U-Nets. BrainLes@MICCAI (2) 2019: 179-190 - [c62]Aleksandra Kardas, Michal Kawulok, Jakub Nalepa:
On Evolutionary Classification Ensembles. CEC 2019: 2974-2981 - [c61]Szymon Piechaczek, Michal Kawulok, Jakub Nalepa:
Memetic Evolution of Classification Ensembles. EvoApplications 2019: 299-307 - [c60]Wojciech Dudzik, Michal Kawulok, Jakub Nalepa:
Evolutionarily-tuned support vector machines. GECCO (Companion) 2019: 165-166 - [c59]Jakub Nalepa, Marcin Cwiek, Wojciech Dudzik, Michal Kawulok, Michael P. Hayball, Grzegorz Mrukwa, Szymon Piechaczek, Pablo Ribalta Lorenzo, Michal Marcinkiewicz, Barbara Bobek-Billewicz, Pawel Wawrzyniak, Pawel Ulrych, Janusz Szymanek:
Data Augmentation via Image Registration. ICIP 2019: 4250-4254 - [c58]Wojciech Dudzik, Michal Kawulok, Jakub Nalepa:
Optimizing Training Data and Hyperparameters of Support Vector Machines Using a Memetic Algorithm. ICMMI 2019: 229-238 - [c57]Michal Kawulok, Szymon Piechaczek, Krzysztof Hrynczenko, Pawel Benecki, Daniel Kostrzewa, Jakub Nalepa:
On Training Deep Networks for Satellite Image Super-Resolution. IGARSS 2019: 3125-3128 - [c56]Michal Marcinkiewicz, Michal Kawulok, Jakub Nalepa:
Segmentation of Multispectral Data Simulated from Hyperspectral Imagery. IGARSS 2019: 3336-3339 - [i12]Michal Kawulok, Pawel Benecki, Szymon Piechaczek, Krzysztof Hrynczenko, Daniel Kostrzewa, Jakub Nalepa:
Deep Learning for Multiple-Image Super-Resolution. CoRR abs/1903.00440 (2019) - [i11]Jakub Nalepa, Michal Myller, Michal Kawulok:
Hyperspectral Data Augmentation. CoRR abs/1903.05580 (2019) - [i10]Michal Kawulok, Szymon Piechaczek, Krzysztof Hrynczenko, Pawel Benecki, Daniel Kostrzewa, Jakub Nalepa:
On training deep networks for satellite image super-resolution. CoRR abs/1906.06697 (2019) - [i9]Jakub Nalepa, Michal Myller, Michal Kawulok:
Transfer Learning for Segmenting Dimensionally-Reduced Hyperspectral Images. CoRR abs/1906.09631 (2019) - [i8]Jakub Nalepa, Pablo Ribalta Lorenzo, Michal Marcinkiewicz, Barbara Bobek-Billewicz, Pawel Wawrzyniak, Maksym Walczak, Michal Kawulok, Wojciech Dudzik, Grzegorz Mrukwa, Pawel Ulrych, Michael P. Hayball:
Fully-automated deep learning-powered system for DCE-MRI analysis of brain tumors. CoRR abs/1907.08303 (2019) - [i7]Jakub Nalepa, Michal Myller, Yasuteru Imai, Ken-ichi Honda, Tomomi Takeda, Marek Antoniak:
Unsupervised Segmentation of Hyperspectral Images Using 3D Convolutional Autoencoders. CoRR abs/1907.08870 (2019) - [i6]Jakub Nalepa, Lukasz Tulczyjew, Michal Myller, Michal Kawulok:
Segmenting Hyperspectral Images Using Spectral-Spatial Convolutional Neural Networks With Training-Time Data Augmentation. CoRR abs/1907.11935 (2019) - 2018
- [j8]Jakub Nalepa, Miroslaw Blocho:
Adaptive cooperation in parallel memetic algorithms for rich vehicle routing problems. Int. J. Grid Util. Comput. 9(2): 179-192 (2018) - [c55]Michal Kawulok, Pawel Benecki, Jakub Nalepa, Daniel Kostrzewa, Lukasz Skonieczny:
Towards Robust Evaluation of Super-Resolution Satellite Image Reconstruction. ACIIDS (1) 2018: 476-486 - [c54]Jakub Nalepa, Michal Myller, Szymon Piechaczek, Krzysztof Hrynczenko, Michal Kawulok:
Genetic Selection of Training Sets for (Not Only) Artificial Neural Networks. BDAS 2018: 194-206 - [c53]Pablo Ribalta Lorenzo, Michal Marcinkiewicz, Jakub Nalepa:
Segmentation of Hyperspectral Images Using Quantized Convolutional Neural Networks. DSD 2018: 260-267 - [c52]Jakub Nalepa, Grzegorz Mrukwa, Michal Kawulok:
Evolvable Deep Features. EvoApplications 2018: 497-505 - [c51]Jakub Nalepa, Miroslaw Blocho:
Parameter-less (meta)heuristics for vehicle routing problems. GECCO (Companion) 2018: 27-28 - [c50]Krzysztof Pawelczyk, Michal Kawulok, Jakub Nalepa:
Genetically-trained deep neural networks. GECCO (Companion) 2018: 63-64 - [c49]Pablo Ribalta Lorenzo, Jakub Nalepa:
Memetic evolution of deep neural networks. GECCO 2018: 505-512 - [c48]Jakub Nalepa, Michael P. Hayball, Stephen J. Brown, Michal Kawulok, Janusz Szymanek:
Extracting Biomarkers from Dynamic Images - Approaches and Challenges. ICPRAM 2018: 520-525 - [c47]Jakub Nalepa, Piotr Mokry, Janusz Szymanek, Michael P. Hayball:
Transferring Information Across Medical Images of Different Modalities. ICPRAM 2018: 526-533 - [c46]Wojciech Dudzik, Jakub Nalepa, Michal Kawulok:
Automated Optimization of Non-linear Support Vector Machines for Binary Classification. INCoS 2018: 504-513 - [c45]Jakub Nalepa, Szymon Piechaczek, Michal Myller, Krzysztof Hrynczenko:
Multi-scale Voting Classifiers for Breast-Cancer Histology Images. INCoS 2018: 526-534 - [c44]Michal Marcinkiewicz, Jakub Nalepa, Pablo Ribalta Lorenzo, Wojciech Dudzik, Grzegorz Mrukwa:
Segmenting Brain Tumors from MRI Using Cascaded Multi-modal U-Nets. BrainLes@MICCAI (2) 2018: 13-24 - [i5]Pablo Ribalta Lorenzo, Lukasz Tulczyjew, Michal Marcinkiewicz, Jakub Nalepa:
Band Selection from Hyperspectral Images Using Attention-based Convolutional Neural Networks. CoRR abs/1811.02667 (2018) - [i4]Jakub Nalepa, Michal Myller, Michal Kawulok:
Validating Hyperspectral Image Segmentation. CoRR abs/1811.03707 (2018) - 2017
- [j7]Jakub Nalepa, Miroslaw Blocho:
Adaptive guided ejection search for pickup and delivery with time windows. J. Intell. Fuzzy Syst. 32(2): 1547-1559 (2017) - [c43]Jakub Nalepa, Pablo Ribalta Lorenzo:
Convergence Analysis of PSO for Hyper-Parameter Selection in Deep Neural Networks. 3PGCIC 2017: 284-295 - [c42]Marcin Cwiek, Jakub Nalepa:
Spatial Planning as a Hexomino Puzzle. ACIIDS (1) 2017: 410-420 - [c41]Maksym Walczak, Izabela Burda, Jakub Nalepa, Michal Kawulok:
Segmenting Lungs from Whole-Body CT Scans. BDAS 2017: 403-414 - [c40]Pablo Ribalta Lorenzo, Jakub Nalepa, Luciano Sánchez Ramos, José Ranilla Pastor:
Hands-Free Research Workflow. EASE 2017: 70-73 - [c39]Miroslaw Blocho, Jakub Nalepa:
LCS-Based Selective Route Exchange Crossover for the Pickup and Delivery Problem with Time Windows. EvoCOP 2017: 124-140 - [c38]Pablo Ribalta Lorenzo, Jakub Nalepa, Michal Kawulok, Luciano Sánchez Ramos, José Ranilla Pastor:
Particle swarm optimization for hyper-parameter selection in deep neural networks. GECCO 2017: 481-488 - [c37]Pablo Ribalta Lorenzo, Jakub Nalepa, Luciano Sánchez Ramos, José Ranilla Pastor:
Hyper-parameter selection in deep neural networks using parallel particle swarm optimization. GECCO (Companion) 2017: 1864-1871 - [c36]Krzysztof Pawelczyk, Michal Kawulok, Jakub Nalepa, Michael P. Hayball, Sarah J. McQuaid, Vineet Prakash, Balaji Ganeshan:
Towards Detecting High-Uptake Lesions from Lung CT Scans Using Deep Learning. ICIAP (2) 2017: 310-320 - [c35]Jakub Nalepa, Michal Kawulok, Wojciech Dudzik:
Tuning and Evolving Support Vector Machine Models. ICMMI 2017: 418-428 - [c34]Miroslaw Blocho, Jakub Nalepa:
Complexity Analysis of the Parallel Memetic Algorithm for the Pickup and Delivery Problem with Time Windows. ICMMI 2017: 471-480 - [c33]Jakub Nalepa, Marcin Cwiek, Lukasz Zak:
Behind the Scenes of Deadline24: A Memetic Algorithm for the Modified Job Shop Scheduling Problem. ICMMI 2017: 502-512 - [c32]Michal Kawulok, Jakub Nalepa, Wojciech Dudzik:
An Alternating Genetic Algorithm for Selecting SVM Model and Training Set. MCPR 2017: 94-104 - [c31]Jakub Nalepa, Miroslaw Blocho:
A Parallel Memetic Algorithm for the Pickup and Delivery Problem with Time Windows. PDP 2017: 1-8 - [i3]Miroslaw Blocho, Jakub Nalepa:
Complexity Analysis of the Parallel Guided Ejection Search for the Pickup and Delivery Problem with Time Windows. CoRR abs/1704.06724 (2017) - 2016
- [j6]Michal Kawulok, Jolanta Kawulok, Jakub Nalepa, Bogdan Smolka:
Hybrid adaptation for detecting skin in color images. Intell. Data Anal. 20(s1): S121-S139 (2016) - [j5]Jakub Nalepa, Michal Kawulok:
Adaptive memetic algorithm enhanced with data geometry analysis to select training data for SVMs. Neurocomputing 185: 113-132 (2016) - [j4]Jakub Nalepa, Miroslaw Blocho:
Adaptive memetic algorithm for minimizing distance in the vehicle routing problem with time windows. Soft Comput. 20(6): 2309-2327 (2016) - [c30]Jakub Nalepa, Miroslaw Blocho:
Temporally Adaptive Co-operation Schemes. 3PGCIC 2016: 145-156 - [c29]Jakub Nalepa, Miroslaw Blocho:
Enhanced Guided Ejection Search for the Pickup and Delivery Problem with Time Windows. ACIIDS (1) 2016: 388-398 - [c28]Marcin Cwiek, Jakub Nalepa, Marcin Dublanski:
How to Generate Benchmarks for Rich Routing Problems? ACIIDS (1) 2016: 399-409 - [c27]Maciej Papiez, Michal Kawulok, Jakub Nalepa:
Manifold Learning for Hand Pose Recognition: Evaluation Framework. BDAS 2016: 704-715 - [c26]Jakub Nalepa, Miroslaw Blocho:
Is Your Parallel Algorithm Correct? FedCSIS (Position Papers) 2016: 87-93 - [c25]Jakub Nalepa, Michal Kawulok:
The Smaller, the Better: Selecting Refined SVM Training Sets Using Adaptive Memetic Algorithm. GECCO (Companion) 2016: 165-166 - [c24]Michal Kawulok, Jakub Nalepa, Karolina Nurzynska, Bogdan Smolka:
In Search of Truth: Analysis of Smile Intensity Dynamics to Detect Deception. IBERAMIA 2016: 325-337 - 2015
- [j3]Jakub Nalepa, Miroslaw Blocho:
Co-operation in the Parallel Memetic Algorithm. Int. J. Parallel Program. 43(5): 812-839 (2015) - [c23]Jakub Nalepa, Miroslaw Blocho:
A Parallel Algorithm with the Search Space Partition for the Pickup and Delivery with Time Windows. 3PGCIC 2015: 92-99 - [c22]Jakub Nalepa, Krzysztof Siminski, Michal Kawulok:
Towards parameter-less support vector machines. ACPR 2015: 211-215 - [c21]Michal Kawulok, Jakub Nalepa:
Towards robust SVM training from weakly labeled large data sets. ACPR 2015: 464-468 - [c20]Miroslaw Blocho, Jakub Nalepa:
Impact of Parallel Memetic Algorithm Parameters on Its Efficacy. BDAS 2015: 299-308 - [c19]Jakub Nalepa, Janusz Szymanek, Michal Kawulok:
Real-Time People Counting from Depth Images. BDAS 2015: 387-397 - [c18]Jakub Nalepa, Marcin Cwiek, Michal Kawulok:
Adaptive memetic algorithm for the job shop scheduling problem. IJCNN 2015: 1-8 - [c17]Miroslaw Blocho, Jakub Nalepa:
A Parallel Algorithm for Minimizing the Fleet Size in the Pickup and Delivery Problem with Time Windows. EuroMPI 2015: 15:1-15:2 - 2014
- [j2]Michal Kawulok, Jolanta Kawulok, Jakub Nalepa, Bogdan Smolka:
Self-adaptive algorithm for segmenting skin regions. EURASIP J. Adv. Signal Process. 2014: 170 (2014) - [j1]Michal Kawulok, Jolanta Kawulok, Jakub Nalepa:
Spatial-based skin detection using discriminative skin-presence features. Pattern Recognit. Lett. 41: 3-13 (2014) - [c16]Jakub Nalepa, Michal Kawulok:
Fast and Accurate Hand Shape Classification. BDAS 2014: 364-373 - [c15]Michal Kawulok, Jolanta Kawulok, Jakub Nalepa, Bogdan Smolka:
Self-Adaptive Skin Segmentation in Color Images. CIARP 2014: 96-103 - [c14]Jakub Nalepa, Michal Kawulok:
Adaptive Genetic Algorithm to Select Training Data for Support Vector Machines. EvoApplications 2014: 514-525 - [c13]Jakub Nalepa, Michal Kawulok:
A memetic algorithm to select training data for support vector machines. GECCO 2014: 573-580 - [c12]Marcin Cwiek, Jakub Nalepa:
A fast genetic algorithm for the flexible job shop scheduling problem. GECCO (Companion) 2014: 1449-1450 - [c11]Jakub Nalepa:
Adaptive memetic algorithm for the vehicle routing problem with time windows. GECCO (Companion) 2014: 1467-1468 - [c10]Michal Kawulok, Jakub Nalepa:
Dynamically Adaptive Genetic Algorithm to Select Training Data for SVMs. IBERAMIA 2014: 242-254 - [c9]Jakub Nalepa, Janusz Szymanek, Michael P. Hayball, Stephen J. Brown, Balaji Ganeshan, Kenneth Miles:
Texture Analysis for Identifying Heterogeneity in Medical Images. ICCVG 2014: 446-453 - [c8]Michal Kawulok, Jakub Nalepa:
Hand pose estimation using support vector machines with evolutionary training. IWSSIP 2014: 87-90 - [i2]Jakub Nalepa, Michal Kawulok:
Real-Time Hand Shape Classification. CoRR abs/1402.2673 (2014) - [i1]Jakub Nalepa, Zbigniew J. Czech:
A Parallel Memetic Algorithm to Solve the Vehicle Routing Problem with Time Windows. CoRR abs/1402.6942 (2014) - 2013
- [c7]Tomasz Grzejszczak, Jakub Nalepa, Michal Kawulok:
Real-Time Wrist Localization in Hand Silhouettes. CORES 2013: 439-449 - [c6]Jakub Nalepa, Zbigniew J. Czech:
New Selection Schemes in a Memetic Algorithm for the Vehicle Routing Problem with Time Windows. ICANNGA 2013: 396-405 - [c5]Michal Kawulok, Jolanta Kawulok, Jakub Nalepa, Maciej Papiez:
Skin detection using spatial analysis with adaptive seed. ICIP 2013: 3720-3724 - [c4]Jakub Nalepa, Tomasz Grzejszczak, Michal Kawulok:
Wrist Localization in Color Images for Hand Gesture Recognition. ICMMI 2013: 79-86 - [c3]Jakub Nalepa, Michal Kawulok:
Parallel Hand Shape Classification. ISM 2013: 401-402 - [c2]Jakub Nalepa, Miroslaw Blocho, Zbigniew J. Czech:
Co-operation Schemes for the Parallel Memetic Algorithm. PPAM (1) 2013: 191-201 - 2012
- [c1]Michal Kawulok, Jakub Nalepa:
Support Vector Machines Training Data Selection Using a Genetic Algorithm. SSPR/SPR 2012: 557-565
Coauthor Index
[j37] [j31] [c111] [c103] [c102] [c98] [i24] [i21] [j29] [j28] [c97] [c93] [c91] [c90] [c87] [c86] [c85] [c84] [c83] [i17] [i16] [i14] [i13] [j25] [j24] [j23] [j21] [c79] [c76] [c75] [j18] [j17] [j16] [j15] [c74] [c72] [c71] [c70] [c69] [c67] [c66] [j12] [j11] [j10] [j9] [c65] [c62] [c61] [c60] [c59] [c58] [c57] [c56] [i12] [i11] [i10] [i9] [i8] [i6] [c55] [c54] [c52] [c50] [c48] [c46] [i4] [c41] [c38] [c36] [c35] [c32] [j6] [j5] [c27] [c25] [c24] [c22] [c21] [c19] [c18] [j2] [j1] [c16] [c15] [c14] [c13] [c10] [c8] [i2] [c7] [c5] [c4] [c3] [c1]
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