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Pasquale Foggia

Pasquale Foggia

D-Index & Metrics

Computer Science

D-Index
39
Citations
10349
World Ranking
9545
National Ranking
274

Overview

Pasquale Foggia is affiliated with the University of Salerno in Italy and works primarily within the field of Computer Science. Their research spans multiple subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Computer Networks and Communications, and Molecular Biology. The focus areas of their work encompass Graph Theory and Algorithms, Network Security and Intrusion Detection, Advanced Malware Detection Techniques, Speech Recognition and Synthesis, Advanced Graph Neural Networks, Anomaly Detection Techniques and Applications, and Face Recognition and Analysis.

Foggia has contributed extensively to the academic literature with a collection of recent papers covering various aspects of artificial intelligence and cognitive computing. Some notable publications include:

  • Multi-task learning on the edge for effective gender, age, ethnicity and emotion recognition (2022) published in Engineering Applications of Artificial Intelligence
  • A Social Robot Architecture for Personalized Real-Time Human-Robot Interaction (2023) published in IEEE Internet of Things Journal
  • Identity, Gender, Age, and Emotion Recognition from Speaker Voice with Multi-task Deep Networks for Cognitive Robotics (2024) published in Cognitive Computation

Foggia also appears in collaborative research contexts, sharing authorship with frequent co-authors such as Mario Vento, Vincenzo Carletti, Antonio Greco, Alessia Saggese, and Antonio Roberto. These collaborations reflect ongoing work across diverse yet interconnected domains in computer science and its applications. Publications are often found in venues like Pattern Recognition Letters, Engineering Applications of Artificial Intelligence, IEEE Internet of Things Journal, Cognitive Computation, and the International Journal on Semantic Web and Information Systems.

In addition to journal articles, Foggia has contributed to book publications, including a work released by the Centre National de la Recherche Scientifique focusing on graph-based representations within pattern recognition, indicating engagement with both theoretical and applied research frameworks.

Overall, Pasquale Foggia's research portfolio highlights a combination of machine learning, multi-task deep networks, and applied artificial intelligence techniques with applications in areas such as facial and speech recognition, cognitive robotics, and network security.

Best Publications

  • THIRTY YEARS OF GRAPH MATCHING IN PATTERN RECOGNITION

    Donatello Conte;Pasquale Foggia;Carlo Sansone;Mario Vento

  • A (sub)graph isomorphism algorithm for matching large graphs

    L.P. Cordella;P. Foggia;C. Sansone;M. Vento

  • An Improved Algorithm for Matching Large Graphs

    L. P. Cordella;P. Foggia;C. Sansone;M. Vento

  • Real-Time Fire Detection for Video-Surveillance Applications Using a Combination of Experts Based on Color, Shape, and Motion

    Pasquale Foggia;Alessia Saggese;Mario Vento

  • GRAPH MATCHING AND LEARNING IN PATTERN RECOGNITION IN THE LAST 10 YEARS

    Pasquale Foggia;Gennaro Percannella;Mario Vento

  • Performance evaluation of the VF graph matching algorithm

    L.P. Cordella;P. Foggia;C. Sansone;M. Vento

  • Audio Surveillance of Roads: A System for Detecting Anomalous Sounds

    Pasquale Foggia;Nicolai Petkov;Alessia Saggese;Nicola Strisciuglio

  • Benchmarking HEp-2 Cells Classification Methods

    Pasquale Foggia;Gennaro Percannella;Paolo Soda;Mario Vento

  • A Performance Comparison of Five Algorithms for Graph Isomorphism

    P. Foggia;C.Sansone;M. Vento

  • Reliable detection of audio events in highly noisy environments

    Pasquale Foggia;Nicolai Petkov;Alessia Saggese;Nicola Strisciuglio

  • Challenging the Time Complexity of Exact Subgraph Isomorphism for Huge and Dense Graphs with VF3

    Vincenzo Carletti;Pasquale Foggia;Alessia Saggese;Mario Vento

  • A Database of Graphs for Isomorphism and Sub-Graph Isomorphism Benchmarking

    Pasquale Foggia;C Sansone;Mario Vento

  • A Comparison of Algorithms for Maximum Common Subgraph on Randomly Connected Graphs

    Horst Bunke;Pasquale Foggia;C. Guidobaldi;Carlo Sansone

  • Challenging Complexity of Maximum Common Subgraph Detection Algorithms: A Performance Analysis of Three Algorithms on a Wide Database of Graphs

    Donatello Conte;Pasquale Foggia;Mario Vento

  • A large database of graphs and its use for benchmarking graph isomorphism algorithms

    M. De Santo;P. Foggia;C. Sansone;M. Vento

  • Reliability Parameters to Improve Combination Strategies in Multi-Expert Systems

    L. P. Cordella;Pasquale Foggia;C. Sansone;F. Tortorella

  • Pattern recognition in stained HEp-2 cells: Where are we now?

    Pasquale Foggia;Gennaro Percannella;Alessia Saggese;Mario Vento

  • Graph edit distance as a quadratic assignment problem

    Sbastien Bougleux;Luc Brun;Vincenzo Carletti;Pasquale Foggia

  • A Method for Counting People in Crowded Scenes

    D. Conte;P. Foggia;G. Percannella;F. Tufano

  • Subgraph Transformations for the Inexact Matching of Attributed Relational Graphs

    Luigi P. Cordella;Pasquale Foggia;Carlo Sansone;Mario Vento

  • Graph clustering using the weighted minimum common supergraph

    Horst Bunke;P. Foggia;C. Guidobaldi;M. Vento

Frequent Co-Authors

Mario Vento
Mario Vento University of Salerno
Carlo Sansone
Carlo Sansone University of Naples Federico II
Nicolai Petkov
Nicolai Petkov University of Groningen
Horst Bunke
Horst Bunke University of Bern
Piergiulio Cappelletti
Piergiulio Cappelletti University of Naples Federico II
Xiaoyi Jiang
Xiaoyi Jiang University of Münster
Josep Lladós
Josep Lladós Autonomous University of Barcelona

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