Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Grabowski, Bartosz"'
Cloud Detection in Multispectral Satellite Images Using Support Vector Machines With Quantum Kernels
Autor:
Miroszewski, Artur, Mielczarek, Jakub, Szczepanek, Filip, Czelusta, Grzegorz, Grabowski, Bartosz, Saux, Bertrand Le, Nalepa, Jakub
Support vector machines (SVMs) are a well-established classifier effectively deployed in an array of pattern recognition and classification tasks. In this work, we consider extending classic SVMs with quantum kernels and applying them to satellite da
Externí odkaz:
http://arxiv.org/abs/2307.07281
Autor:
Miroszewski, Artur, Mielczarek, Jakub, Szczepanek, Filip, Czelusta, Grzegorz, Grabowski, Bartosz, Saux, Bertrand Le, Nalepa, Jakub
The optimization of Kernel-Target Alignment (TA) has been recently proposed as a way to reduce the number of hardware resources in quantum classifiers. It allows to exchange highly expressive and costly circuits to moderate size, task oriented ones.
Externí odkaz:
http://arxiv.org/abs/2306.14515
Autor:
Grabowski, Bartosz, Ziaja, Maciej, Kawulok, Michal, Bosowski, Piotr, Longépé, Nicolas, Saux, Bertrand Le, Nalepa, Jakub
Cloud detection is a pivotal satellite image pre-processing step that can be performed both on the ground and on board a satellite to tag useful images. In the latter case, it can reduce the amount of data to downlink by pruning the cloudy areas, or
Externí odkaz:
http://arxiv.org/abs/2306.09886
Autor:
Miroszewski, Artur, Mielczarek, Jakub, Czelusta, Grzegorz, Szczepanek, Filip, Grabowski, Bartosz, Saux, Bertrand Le, Nalepa, Jakub
Support vector machines (SVMs) are a well-established classifier effectively deployed in an array of classification tasks. In this work, we consider extending classical SVMs with quantum kernels and applying them to satellite data analysis. The desig
Externí odkaz:
http://arxiv.org/abs/2302.08270
Autor:
Grabowski, Bartosz, Głomb, Przemysław, Masarczyk, Wojciech, Pławiak, Paweł, Yıldırım, Özal, Acharya, U Rajendra, Tan, Ru-San
Interpretation of electrocardiography (ECG) signals is required for diagnosing cardiac arrhythmia. Recently, machine learning techniques have been applied for automated computer-aided diagnosis. Machine learning tasks can be divided into regression a
Externí odkaz:
http://arxiv.org/abs/2210.14253
Autor:
Grabowski, Bartosz, Ziaja, Maciej, Kawulok, Michal, Longépé, Nicolas, Saux, Bertrand Le, Nalepa, Jakub
Cloud detection is a pivotal satellite image pre-processing step that can be performed both on the ground and on board a satellite to tag useful images. In the latter case, it can help to reduce the amount of data to downlink by pruning the cloudy ar
Externí odkaz:
http://arxiv.org/abs/2210.13659
Autor:
Książek, Kamil, Głomb, Przemysław, Romaszewski, Michał, Cholewa, Michał, Grabowski, Bartosz, Búza, Krisztián
Neural networks, in particular autoencoders, are one of the most promising solutions for unmixing hyperspectral data, i.e. reconstructing the spectra of observed substances (endmembers) and their relative mixing fractions (abundances), which is neede
Externí odkaz:
http://arxiv.org/abs/2109.13748
Autor:
Grabowski, Bartosz, Ziaja, Maciej, Kawulok, Michal, Bosowski, Piotr, Longépé, Nicolas, Le Saux, Bertrand, Nalepa, Jakub
Publikováno v:
In Engineering Applications of Artificial Intelligence June 2024 132
Publikováno v:
Remote Sens. 2020, 12, 2653
Hyperspectral imaging is a rich source of data, allowing for multitude of effective applications. However, such imaging remains challenging because of large data dimension and, typically, small pool of available training examples. While deep learning
Externí odkaz:
http://arxiv.org/abs/1909.05507
Publikováno v:
In Journal of Cultural Heritage May-June 2018 31:1-12