Abilità e competenze del docente di sostegno

Qualitative Imaging of Experimental Multistatic Ground Penetrating Radar Data

Subsurface imaging of unknown buried objects is of fundamental importance in several fields, spanning from civil engineering applications to safety and biomedical issues. The detection of objects located in an investigation domain in a nondestructive fashion can be faced via addressing an electromagnetic inverse scattering problem. In this paper, an experimental assessment of a simple, linear approach, known as linear sampling method (LSM), is proposed. The results show good recovery performa...

Convolutional Neural Networks for Tomographic MIMO Ground Penetrating Radar Imaging

Ground penetrating radar (GPR) represents a remote sensing modality which has been extensively exploited for the detection and characterisation of buried objects in a non-destructive way. To this aim, several algorithms have been developed to efficiently and automatically identify underground targets of interest. In this framework, approaches based on deep learning and convolutional neural networks (CNNs) have been proposed in the past years and recently gained a lot of attention by the scien...

Neural networks for optimal initial guess selection in nonlinear microwave subsurface imaging

Subsurface non-destructive exploration is of interest for several applications which span from archeology and civil engineering to safety and security. Among the available remote sensing imaging modalities, ground penetrating radar (GPR) seems very attractive for the detection and characterisation of buried targets. This technology exploits electromagnetic signals in the microwave band to perform the exploration in a non-invasive way. Unfortunately, conventional GPR images require an expert u...