D-Index & Metrics Best Publications
Computer Science
UK
2023

D-Index & Metrics 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.

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 75 Citations 19,588 489 World Ranking 852 National Ranking 55

Research.com Recognitions

Awards & Achievements

2023 - Research.com Computer Science in United Kingdom Leader Award

2015 - Distinguished Fellow of the British Machine Vision Association (BMVA)

2008 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to biometrics and computer vision.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Statistics

The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Biometrics, Gait and Feature extraction. His work carried out in the field of Artificial intelligence brings together such families of science as Gait, Identification, Gait analysis and Pattern recognition. His Computer vision research focuses on subjects like Artificial neural network, which are linked to Stick figure.

His study in Biometrics is interdisciplinary in nature, drawing from both Signature, Speech recognition and Field. His Gait study combines topics from a wide range of disciplines, such as Motion, Fourier transform, Process and Pattern recognition. His studies deal with areas such as Curse of dimensionality, Maxima and minima, Motion analysis, Feature vector and Invariant as well as Feature extraction.

His most cited work include:

  • Feature Extraction and Image Processing (612 citations)
  • WirelessHART: Applying Wireless Technology in Real-Time Industrial Process Control (483 citations)
  • Automatic extraction and description of human gait models for recognition purposes (367 citations)

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

Mark S. Nixon mainly focuses on Artificial intelligence, Computer vision, Biometrics, Pattern recognition and Gait. His research on Artificial intelligence often connects related areas such as Gait analysis. His study in Noise, Image, Motion, Feature and Edge detection falls under the purview of Computer vision.

His studies in Biometrics integrate themes in fields like Machine learning, Speech recognition and Identification. Mark S. Nixon combines subjects such as Contextual image classification and Face with his study of Pattern recognition. His Gait research integrates issues from Gait, Silhouette and Pattern recognition.

He most often published in these fields:

  • Artificial intelligence (69.46%)
  • Computer vision (49.90%)
  • Biometrics (31.74%)

What were the highlights of his more recent work (between 2012-2021)?

  • Artificial intelligence (69.46%)
  • Biometrics (31.74%)
  • Computer vision (49.90%)

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

His primary scientific interests are in Artificial intelligence, Biometrics, Computer vision, Soft biometrics and Pattern recognition. His Artificial intelligence research incorporates elements of Gait and Machine learning. His research in Biometrics intersects with topics in Facial recognition system, Face and Identification.

His Computer vision research includes themes of Cluster analysis and Robustness. His Soft biometrics study combines topics from a wide range of disciplines, such as Quality, Field, Categorical variable, Set and Semantics. His work carried out in the field of Pattern recognition brings together such families of science as Focus and Feature.

Between 2012 and 2021, his most popular works were:

  • A survey on ear biometrics (170 citations)
  • Handbook of Biometric Anti-Spoofing: Trusted Biometrics under Spoofing Attacks (116 citations)
  • Soft Biometrics and Their Application in Person Recognition at a Distance (103 citations)

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

  • Artificial intelligence
  • Computer vision
  • Statistics

Mark S. Nixon focuses on Biometrics, Artificial intelligence, Soft biometrics, Computer vision and Identification. The concepts of his Biometrics study are interwoven with issues in Gait and Facial recognition system, Face. His Gait study integrates concerns from other disciplines, such as Gait and Silhouette.

His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning and Pattern recognition. His studies deal with areas such as Field and Human–computer interaction as well as Computer vision. His Feature extraction study combines topics in areas such as Histogram and Data science.

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

Feature Extraction and Image Processing

Mark S. Nixon;Alberto S. Aguado.
(2002)

955 Citations

WirelessHART: Applying Wireless Technology in Real-Time Industrial Process Control

Jianping Song;Song Han;A.K. Mok;Deji Chen.
real time technology and applications symposium (2008)

779 Citations

Audio- and Video-Based Biometric Person Authentication

Josef Kittler;Mark S. Nixon.
(2003)

776 Citations

Automatic extraction and description of human gait models for recognition purposes

David Cunado;Mark S. Nixon;John N. Carter.
Computer Vision and Image Understanding (2003)

581 Citations

Human Identification Based on Gait

Mark S. Nixon;Tieniu N. Tan;Rama Chellappa.
(2005)

493 Citations

Automated person recognition by walking and running via model-based approaches

Chew Yean Yam;Mark S Nixon;John N Carter.
Pattern Recognition (2004)

438 Citations

Super-resolution target identification from remotely sensed images using a Hopfield neural network

A.J. Tatem;H.G. Lewis;P.M. Atkinson;M.S. Nixon.
IEEE Transactions on Geoscience and Remote Sensing (2001)

416 Citations

Force field feature extraction for ear biometrics

David J. Hurley;Mark S. Nixon;John N. Carter.
Computer Vision and Image Understanding (2005)

382 Citations

Using Gait as a Biometric, via Phase-weighted Magnitude Spectra

David Cunado;Mark S. Nixon;John N. Carter.
AVBPA '97 Proceedings of the First International Conference on Audio- and Video-Based Biometric Person Authentication (1997)

345 Citations

On a Large Sequence-Based Human Gait Database

Jamie Shutler;Mike Grant;Mark S Nixon;John N Carter.
(2004)

336 Citations

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