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D-Index & Metrics

Computer Science

D-Index
43
Citations
7491
World Ranking
8009
National Ranking
213

Overview

Michele Nappi is affiliated with the University of Salerno in Italy. Their research primarily focuses on computer science, with a significant emphasis on computer vision and pattern recognition. They have contributed extensively to related subfields including artificial intelligence, signal processing, radiology, nuclear medicine and imaging, as well as computer networks and communications.

The scientist's recent scholarly publications cover a range of topics and have appeared in various academic venues. Notable papers include: Improving the Prediction of Heart Failure Patients' Survival Using SMOTE and Effective Data Mining Techniques (2021, IEEE Access), Impact of convolutional neural network and FastText embedding on text classification (2022, Multimedia Tools and Applications), Emotion Recognition by Textual Tweets Classification Using Voting Classifier (LR-SGD) (2020, IEEE Access), Discrepancy detection between actual user reviews and numeric ratings of Google App store using deep learning (2021, Expert Systems with Applications), and Facial expression recognition with trade-offs between data augmentation and deep learning features (2021, Journal of Ambient Intelligence and Humanized Computing).

Their collaborations include frequent work with several co-authors. Among the most frequent are Lucia Cascone, Muhammad Umer, Chiara Pero, Aniello Castiglione, and Fabio Narducci, each contributing to numerous joint publications.

Michele Nappi's work is regularly published in several specialized venues. These include:

  • Pattern Recognition Letters
  • IEEE Access
  • Journal of Ambient Intelligence and Humanized Computing
  • IEEE Transactions on Industrial Informatics
  • IEEE Journal of Biomedical and Health Informatics

The main topics covered in their research relate to:

  • Face recognition and analysis
  • Face and expression recognition
  • Biometric identification and security
  • Video surveillance and tracking methods
  • COVID-19 diagnosis using AI
  • AI in cancer detection
  • Advanced neural network applications

This extensive body of work places Michele Nappi at the intersection of advanced computational techniques and practical applications in health, security, and multimedia analysis. Their focus on neural networks, machine learning for health diagnostics, and biometric systems reflects ongoing trends within artificial intelligence and computer vision research fields.

Best Publications

  • 2D and 3D face recognition: A survey

    Andrea F. Abate;Michele Nappi;Daniel Riccio;Gabriele Sabatino

  • Improving the Prediction of Heart Failure Patients’ Survival Using SMOTE and Effective Data Mining Techniques

    Abid Ishaq;Saima Sadiq;Muhammad Umer;Saleem Ullah

  • Mobile Iris Challenge Evaluation (MICHE)-I, biometric iris dataset and protocols

    Maria De Marsico;Michele Nappi;Daniel Riccio;Harry Wechsler

  • FIRME: Face and Iris Recognition for Mobile Engagement

    Maria De Marsico;Chiara Galdi;Michele Nappi;Daniel Riccio

  • Speed-up in fractal image coding: comparison of methods

    M. Polvere;M. Nappi

  • Robust Face Recognition for Uncontrolled Pose and Illumination Changes

    M. De Marsico;M. Nappi;D. Riccio;H. Wechsler

  • Impact of convolutional neural network and FastText embedding on text classification

    Unknown

  • Moving face spoofing detection via 3D projective invariants

    Maria De Marsico;Michele Nappi;Daniel Riccio;Jean-Luc Dugelay

  • A range/domain approximation error-based approach for fractal image compression

    R. Distasi;M. Nappi;D. Riccio

  • GANT: Gaze analysis technique for human identification

    Virginio Cantoni;Chiara Galdi;Michele Nappi;Marco Porta

  • Emotion Recognition by Textual Tweets Classification Using Voting Classifier (LR-SGD)

    Anam Yousaf;Muhammad Umer;Saima Sadiq;Saleem Ullah

  • Discrepancy detection between actual user reviews and numeric ratings of Google App store using deep learning

    Saima Sadiq;Muhammad Umer;Muhammad Umer;Saleem Ullah;Seyedali Mirjalili

  • A haptic-based approach to virtual training for aerospace industry

    Andrea F. Abate;Mariano Guida;Paolo Leoncini;Michele Nappi

  • Image compression by B-tree triangular coding

    R. Distasi;M. Nappi;S. Vitulano

  • Facial expression recognition with trade-offs between data augmentation and deep learning features

    Saiyed Umer;Ranjeet Kumar Rout;Chiara Pero;Michele Nappi

  • Multimodal authentication on smartphones

    Chiara Galdi;Michele Nappi;Jean-Luc Dugelay

  • Ear Recognition by means of a Rotation Invariant Descriptor

    A.F. Abate;M. Nappi;D. Riccio;S. Ricciardi

  • COVID-19: Automatic Detection of the Novel Coronavirus Disease From CT Images Using an Optimized Convolutional Neural Network

    Aniello Castiglione;Pandi Vijayakumar;Michele Nappi;Saima Sadiq

  • IoT Based Smart Monitoring of Patients’ with Acute Heart Failure

    Unknown

  • FARO: FAce Recognition Against Occlusions and Expression Variations

    M. De Marsico;M. Nappi;D. Riccio

  • Robust face recognition after plastic surgery using local region analysis

    Maria De Marsico;Michele Nappi;Daniel Riccio;Harry Wechsler

  • Noisy Iris Recognition Integrated Scheme

    Maria De Marsico;Michele Nappi;Daniel Riccio

Frequent Co-Authors

Harry Wechsler
Harry Wechsler George Mason University
Aniello Castiglione
Aniello Castiglione University of Salerno
Genoveffa Tortora
Genoveffa Tortora University of Salerno
Vincenzo Loia
Vincenzo Loia University of Salerno
Kim-Kwang Raymond Choo
Kim-Kwang Raymond Choo The University of Texas at San Antonio
Massimo Tistarelli
Massimo Tistarelli University of Sassari
Pandi Vijayakumar
Pandi Vijayakumar Anna University, Chennai
Julian Fierrez
Julian Fierrez Autonomous University of Madrid
David Zhang
David Zhang Chinese University of Hong Kong, Shenzhen

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