D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 73 Citations 19,290 315 World Ranking 687 National Ranking 9

Research.com Recognitions

Awards & Achievements

2012 - IEEE Fellow For contributions to multiple classifier systems

2004 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to pattern recognition and its applications and multiple classifier systems.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

His primary areas of investigation include Artificial intelligence, Machine learning, Pattern recognition, Classifier and Computer security. His Artificial intelligence study frequently links to adjacent areas such as Malware. His Malware research incorporates elements of Adversary, Adversarial machine learning and Evasion.

His Machine learning research incorporates themes from Training set, Data mining and Robustness. His study focuses on the intersection of Pattern recognition and fields such as Contextual image classification with connections in the field of Backpropagation, Sensor fusion, Remote sensing and Network architecture. His Biometrics study also includes fields such as

  • Fingerprint which connect with Fingerprint recognition,
  • Liveness which intersects with area such as Image texture and Facial recognition system.

His most cited work include:

  • Multiple Classifier Systems (1064 citations)
  • Evasion attacks against machine learning at test time (939 citations)
  • Wild patterns: Ten years after the rise of adversarial machine learning (474 citations)

What are the main themes of his work throughout his whole career to date?

Fabio Roli spends much of his time researching Artificial intelligence, Machine learning, Pattern recognition, Biometrics and Data mining. His study explores the link between Artificial intelligence and topics such as Computer vision that cross with problems in Liveness. His Machine learning research focuses on subjects like Malware, which are linked to Evasion.

His Biometrics study combines topics from a wide range of disciplines, such as Fingerprint, Spoofing attack, Robustness and Fingerprint. His study in Fingerprint is interdisciplinary in nature, drawing from both Fingerprint Verification Competition and Fingerprint recognition. His studies deal with areas such as Image processing and Deep learning as well as Artificial neural network.

He most often published in these fields:

  • Artificial intelligence (73.95%)
  • Machine learning (39.47%)
  • Pattern recognition (35.26%)

What were the highlights of his more recent work (between 2014-2021)?

  • Artificial intelligence (73.95%)
  • Machine learning (39.47%)
  • Malware (9.21%)

In recent papers he was focusing on the following fields of study:

Fabio Roli mostly deals with Artificial intelligence, Machine learning, Malware, Adversarial system and Pattern recognition. His research in Artificial intelligence tackles topics such as Computer vision which are related to areas like Matching. The concepts of his Machine learning study are interwoven with issues in Contextual image classification, Training set and Data mining.

Fabio Roli has included themes like Sandbox, Robustness and Evasion in his Malware study. His Adversarial system research includes elements of Computer security, Exploit and Pattern recognition. His Pattern recognition research includes themes of Fingerprint Verification Competition and Local binary patterns.

Between 2014 and 2021, his most popular works were:

  • Wild patterns: Ten years after the rise of adversarial machine learning (474 citations)
  • Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization (205 citations)
  • Is Feature Selection Secure against Training Data Poisoning (201 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Statistics

His primary scientific interests are in Artificial intelligence, Machine learning, Malware, Adversarial system and Deep learning. His biological study spans a wide range of topics, including Data mining and Pattern recognition. His work carried out in the field of Machine learning brings together such families of science as Classifier, Algorithm design and Training set.

His Malware research is multidisciplinary, incorporating elements of Feature, Linear classifier, Robustness and Evasion. His research investigates the connection with Adversarial system and areas like Computer security which intersect with concerns in Leverage, Phishing and Web page. His Deep learning research incorporates elements of Artificial neural network and Convolutional neural network.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Multiple Classifier Systems

Jón Atli Benediktsson;Josef Kittler;Fabio Roli.
(2008)

1647 Citations

Evasion attacks against machine learning at test time

Battista Biggio;Igino Corona;Davide Maiorca;Blaine Nelson.
european conference on machine learning (2013)

661 Citations

Design of effective neural network ensembles for image classification purposes

Giorgio Giacinto;Fabio Roli.
Image and Vision Computing (2001)

507 Citations

Wild patterns: Ten years after the rise of adversarial machine learning

Battista Biggio;Fabio Roli.
Pattern Recognition (2018)

379 Citations

A theoretical and experimental analysis of linear combiners for multiple classifier systems

G. Fumera;F. Roli.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2005)

354 Citations

Security Evaluation of PatternClassifiers under Attack

Battista Biggio;Giorgio Fumera;Fabio Roli.
IEEE Transactions on Knowledge and Data Engineering (2014)

329 Citations

Dynamic classifier selection based on multiple classifier behaviour

Giorgio Giacinto;Fabio Roli.
Pattern Recognition (2001)

298 Citations

Fusion of multiple classifiers for intrusion detection in computer networks

Giorgio Giacinto;Fabio Roli;Luca Didaci.
Pattern Recognition Letters (2003)

271 Citations

Methods for Designing Multiple Classifier Systems

Fabio Roli;Giorgio Giacinto;Gianni Vernazza.
multiple classifier systems (2001)

261 Citations

An approach to the automatic design of multiple classifier systems

Giorgio Giacinto;Fabio Roli.
machine learning and data mining in pattern recognition (2001)

257 Citations

Best Scientists Citing Fabio Roli

Robert Sabourin

Robert Sabourin

École de Technologie Supérieure

Publications: 93

Lorenzo Bruzzone

Lorenzo Bruzzone

University of Trento

Publications: 46

Giorgio Giacinto

Giorgio Giacinto

University of Cagliari

Publications: 45

Anil K. Jain

Anil K. Jain

Michigan State University

Publications: 41

Carlo Sansone

Carlo Sansone

University of Naples Federico II

Publications: 35

Horst Bunke

Horst Bunke

University of Bern

Publications: 34

Sébastien Marcel

Sébastien Marcel

Idiap Research Institute

Publications: 31

Nicolas Papernot

Nicolas Papernot

University of Toronto

Publications: 29

Josef Kittler

Josef Kittler

University of Surrey

Publications: 28

Luiz S. Oliveira

Luiz S. Oliveira

Federal University of Paraná

Publications: 26

Robert P. W. Duin

Robert P. W. Duin

Delft University of Technology

Publications: 26

Christoph Busch

Christoph Busch

Norwegian University of Science and Technology

Publications: 25

Mohamed S. Kamel

Mohamed S. Kamel

University of Waterloo

Publications: 23

Ludmila I. Kuncheva

Ludmila I. Kuncheva

Bangor University

Publications: 22

Somesh Jha

Somesh Jha

University of Wisconsin–Madison

Publications: 21

Abdenour Hadid

Abdenour Hadid

University of Oulu

Publications: 21

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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