2 citations · 3 across the 6 of their papers we have counts for
4 papers · 2 filters
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…
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…
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…
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…