Neural Network for Nanomaterials Classification | A. Paviglianiti | PitchD 08
Channel: IEEE PoliTO Student Branch
Date: 08/06/2019

PitchD – the PhD’s pitch: our PhD IEEE Student Members explain to students, collegues and professors their research.

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SoCNNet: An Optimized Sobel Filter based Convolutional Neural Network for SEM images Classification of Nanomaterials
Miss Annunziata Paviglianiti, PhD student, DET.

This presentation aims at providing an illustration of my research about an optimized deep Convolutional Neural Network (CNN) for the automatic classification of Scanning Electron Microscope (SEM) images of homogeneous nanofibers (HNF) and nonhomogeneous nanofibers (NHNF) produced by electrospinnig process. Specifically, SEM images are used as input of a Deep Learning (DL) framework consisting of a Sobel filter based pre-processing stage followed by a CNN classifier (SoCNNet). Experimental results of this study demonstrate the potential effectiveness of proposed SoCNNet in the industrial chain of nanofibers production.