activity
20022016
most citedFeature Extraction and Soft Computing Methods for Aerospace Structure Defect Classification

50 citations · 173 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2016★ 50 cited

Feature Extraction and Soft Computing Methods for Aerospace Structure Defect Classification

Gianni D'Angelo, Salvatore Rampone

This study concerns the effectiveness of several techniques and methods of signals processing and data interpretation for the diagnosis of aerospace structure defects. This is done…

cs.NE2016★ 9 cited

Prediction of Seasonal Temperature Using Soft Computing Techniques: Application in Benevento (Southern Italy) Area

Salvatore Rampone, Alessio Valente

In this work two soft computing methods, Artificial Neural Networks and Genetic Programming, are proposed in order to forecast the mean temperature that will occur in future season…

cs.AI2016★ 21 cited

Diagnosis of aerospace structure defects by a HPC implemented soft computing algorithm

Gianni D'Angelo, Salvatore Rampone

This study concerns with the diagnosis of aerospace structure defects by applying a HPC parallel implementation of a novel learning algorithm, named U-BRAIN. The Soft Computing app…

cs.CV2016★ 29 cited

Shape-based defect classification for Non Destructive Testing

Gianni D'Angelo, Salvatore Rampone

The aim of this work is to classify the aerospace structure defects detected by eddy current non-destructive testing. The proposed method is based on the assumption that the defect…

q-bio.QM2016★ 30 cited

Towards a HPC-oriented parallel implementation of a learning algorithm for bioinformatics applications

Gianni D'Angelo, Salvatore Rampone

Background: The huge quantity of data produced in Biomedical research needs sophisticated algorithmic methodologies for its storage, analysis, and processing. High Performance Comp…

astro-ph.IM2014★ 34 cited

Neural Network Aided Glitch-Burst Discrimination and Glitch Classification

Salvatore Rampone, Vincenzo Pierro, Luigi Troiano +1

We investigate the potential of neural-network based classifiers for discriminating gravitational wave bursts (GWBs) of a given canonical family (e.g. core-collapse supernova wavef…