A Face Recognition System Using Off-the-Shelf Feature Extractors and an Ad-Hoc Classifier

  • Stefano MarsiEmail author
  • Luca De Bortoli
  • Francesco Guzzi
  • Jhilik Bhattacharya
  • Francesco Cicala
  • Sergio Carrato
  • Alfredo Canziani
  • Giovanni Ramponi
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 573)


Face recognition systems are of great interest in many applications. We present some results from a comparison on different classification methods using an open source tool that works with Convolutional Neural Networks to extract facial features. This work focuses on the performance obtainable from a multi-class classifier, trained with a reduced number images, to identify a person between a group of known and unknown subjects . The overall system has been implemented in an Odroid XU-4 Platform.


Face detection Face recognition Deep learning Convolutional Neural Networks 



University of Trieste—FRA projects.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Stefano Marsi
    • 1
    Email author
  • Luca De Bortoli
    • 1
  • Francesco Guzzi
    • 1
  • Jhilik Bhattacharya
    • 2
  • Francesco Cicala
    • 1
  • Sergio Carrato
    • 1
  • Alfredo Canziani
    • 3
  • Giovanni Ramponi
    • 1
  1. 1.University of TriesteTriesteItaly
  2. 2.Thapar Institute of Engineering and TechnologyPatialaIndia
  3. 3.New York UniversityNew York CityUSA

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