5 papers
Auto Quantum Machine Learning for Multisource Classification
Tomasz Rybotycki, Sebastian Dziura, Piotr Gawron
With fault-tolerant quantum computing on the horizon, there is growing interest in applying quantum computational methods to data-intensive scientific fields like remote sensing. Q…
On the Importance of Fundamental Properties in Quantum-Classical Machine Learning Models
Silvie Illésová, Tomasz Rybotycki, Piotr Gawron +1
We present a systematic study of how quantum circuit design, specifically the depth of the variational ansatz and the choice of quantum feature mapping, affects the performance of…
Explainable Quantum Machine Learning for Multispectral Images Segmentation: Case Study
Tomasz Rybotycki, Manish K. Gupta, Piotr Gawron
The emergence of Big Data changed how we approach information systems engineering. Nowadays, when we can use remote sensing techniques for Big Data acquisition, the issues such dat…
QMetric: Benchmarking Quantum Neural Networks Across Circuits, Features, and Training Dimensions
Silvie Illésová, Tomasz Rybotycki, Martin Beseda
As hybrid quantum-classical models gain traction in machine learning, there is a growing need for tools that assess their effectiveness beyond raw accuracy. We present QMetric, a P…
Hyperspectral image segmentation with a machine learning model trained using quantum annealer
Dawid Mazur, Tomasz Rybotycki, Piotr Gawron
Training of machine learning models consumes large amounts of energy. Since the energy consumption becomes a major problem in the development and implementation of artificial intel…