@misc{Szymczyk_Piotr_Neural,
 author={Szymczyk, Piotr and Tomecka-Suchoń, Sylwia and Szymczyk, Magdalena},
 howpublished={online},
 publisher={Zielona Góra: Uniwersytet Zielonogórski},
 language={eng},
 abstract={In this article a new neural network based method for automatic classification of ground penetrating radar (GPR) traces is proposed. The presented approach is based on a new representation of GPR signals by polynomials approximation. The coefficients of the polynomial (the feature vector) are neural network inputs for automatic classification of a special kind of geologic structure-a sinkhole. The analysis and results show that the classifier can effectively distinguish sinkholes from other geologic structures.},
 type={artykuł},
 title={Neural networks as a tool for georadar data processing},
 keywords={neural networks, artificial neural networks, ground penetrating radar, classification of a geological structure, sinkhole},
}