126 citations · 552 across the 35 of their papers we have counts for
6 papers · 1 filter
Cloud Detection in Multispectral Satellite Images Using Support Vector Machines With Quantum Kernels
Artur Miroszewski, Jakub Mielczarek, Filip Szczepanek +4
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 extendi…
Optimizing Kernel-Target Alignment for cloud detection in multispectral satellite images
Artur Miroszewski, Jakub Mielczarek, Filip Szczepanek +4
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…
Squeezing nnU-Nets with Knowledge Distillation for On-Board Cloud Detection
Bartosz Grabowski, Maciej Ziaja, Michal Kawulok +4
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…
On the Importance of Sign Labeling: The Hamburg Sign Language Notation System Case Study
Maria Ferlin, Sylwia Majchrowska, Marta Plantykow +4
Labeling is the cornerstone of supervised machine learning, which has been exploited in a plethora of various applications, with sign language recognition being one of them. Howeve…
Detecting Clouds in Multispectral Satellite Images Using Quantum-Kernel Support Vector Machines
Artur Miroszewski, Jakub Mielczarek, Grzegorz Czelusta +4
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 q…
Multitemporal and multispectral data fusion for super-resolution of Sentinel-2 images
Tomasz Tarasiewicz, Jakub Nalepa, Reuben A. Farrugia +4
Multispectral Sentinel-2 images are a valuable source of Earth observation data, however spatial resolution of their spectral bands limited to 10 m, 20 m, and 60 m ground sampling…