H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 35 Citations 6,339 326 World Ranking 5965 National Ranking 43

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Computer vision

His primary areas of investigation include Artificial intelligence, Pattern recognition, Linear discriminant analysis, Machine learning and Computer vision. His Feature vector, Artificial neural network, Facial recognition system, Support vector machine and Principal component analysis investigations are all subjects of Artificial intelligence research. He has researched Pattern recognition in several fields, including Extreme learning machine, Fuzzy set and Feedforward neural network.

The study incorporates disciplines such as Kernel Fisher discriminant analysis, Matching, Class discrimination and Dimensionality reduction in addition to Linear discriminant analysis. He works mostly in the field of Machine learning, limiting it down to topics relating to Classifier and, in certain cases, Database, Speech processing and Face detection. His work focuses on many connections between Computer vision and other disciplines, such as Algorithm, that overlap with his field of interest in Translation and Vertex.

His most cited work include:

  • Exploiting discriminant information in nonnegative matrix factorization with application to frontal face verification (284 citations)
  • Using support vector machines to enhance the performance of elastic graph matching for frontal face authentication (208 citations)
  • Image authentication techniques for surveillance applications (127 citations)

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

Anastasios Tefas spends much of his time researching Artificial intelligence, Pattern recognition, Machine learning, Computer vision and Linear discriminant analysis. All of his Artificial intelligence and Deep learning, Facial recognition system, Feature extraction, Discriminant and Artificial neural network investigations are sub-components of the entire Artificial intelligence study. Anastasios Tefas usually deals with Deep learning and limits it to topics linked to Convolutional neural network and Feature.

Anastasios Tefas focuses mostly in the field of Pattern recognition, narrowing it down to matters related to Cluster analysis and, in some cases, Data mining. Anastasios Tefas focuses mostly in the field of Machine learning, narrowing it down to topics relating to Training set and, in certain cases, Kernel. His Linear discriminant analysis study combines topics in areas such as Kernel Fisher discriminant analysis and Principal component analysis.

He most often published in these fields:

  • Artificial intelligence (83.82%)
  • Pattern recognition (46.57%)
  • Machine learning (27.70%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (83.82%)
  • Machine learning (27.70%)
  • Deep learning (13.97%)

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

Anastasios Tefas mostly deals with Artificial intelligence, Machine learning, Deep learning, Artificial neural network and Pattern recognition. He combines subjects such as Data mining and Computer vision with his study of Artificial intelligence. The Feature learning, Feature and Reinforcement learning research Anastasios Tefas does as part of his general Machine learning study is frequently linked to other disciplines of science, such as Financial market, therefore creating a link between diverse domains of science.

His research integrates issues of Data modeling, Time series, Regularization, Inference and Discriminative model in his study of Deep learning. His research in the fields of Neuromorphic engineering and Recurrent neural network overlaps with other disciplines such as Knowledge transfer and Process. The Pattern recognition study combines topics in areas such as Facial recognition system and Cluster analysis.

Between 2017 and 2021, his most popular works were:

  • Deep convolutional learning for Content Based Image Retrieval (79 citations)
  • Learning Deep Representations with Probabilistic Knowledge Transfer (72 citations)
  • An all-optical neuron with sigmoid activation function. (36 citations)

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

  • Artificial intelligence
  • Machine learning
  • Artificial neural network

Anastasios Tefas mainly investigates Artificial intelligence, Machine learning, Artificial neural network, Deep learning and Convolutional neural network. Anastasios Tefas has included themes like Data modeling, Data mining and Pattern recognition in his Artificial intelligence study. His study on Support vector machine is often connected to Extension as part of broader study in Pattern recognition.

In general Machine learning, his work in Feature vector is often linked to Function linking many areas of study. In the subject of general Artificial neural network, his work in Neuromorphic engineering and Feedforward neural network is often linked to Knowledge transfer, thereby combining diverse domains of study. His Convolutional neural network research integrates issues from Regularization and Content-based image retrieval, Image retrieval.

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

Exploiting discriminant information in nonnegative matrix factorization with application to frontal face verification

S. Zafeiriou;A. Tefas;I. Buciu;I. Pitas.
IEEE Transactions on Neural Networks (2006)

344 Citations

Using support vector machines to enhance the performance of elastic graph matching for frontal face authentication

A. Tefas;C. Kotropoulos;I. Pitas.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2001)

294 Citations

Image authentication techniques for surveillance applications

F. Bartolini;A. Tefas;M. Barni;I. Pitas.
Proceedings of the IEEE (2001)

192 Citations

Blind robust watermarking schemes for copyright protection of 3D mesh objects

S. Zafeiriou;A. Tefas;I. Pitas.
IEEE Transactions on Visualization and Computer Graphics (2005)

185 Citations

Comparison of face verification results on the XM2VTFS database

J. Matas;M. Hamouz;K. Jonsson;J. Kittler.
international conference on pattern recognition (2000)

180 Citations

View-Invariant Action Recognition Based on Artificial Neural Networks

A. Iosifidis;A. Tefas;I. Pitas.
IEEE Transactions on Neural Networks (2012)

161 Citations

Forecasting Stock Prices from the Limit Order Book Using Convolutional Neural Networks

Avraam Tsantekidis;Nikolaos Passalis;Anastasios Tefas;Juho Kanniainen.
ieee conference on business informatics (2017)

159 Citations

Frontal face authentication using morphological elastic graph matching

C. Kotropoulos;A. Tefas;I. Pitas.
IEEE Transactions on Image Processing (2000)

143 Citations

Minimum Class Variance Extreme Learning Machine for Human Action Recognition

Alexandros Iosifidis;Anastasios Tefas;Ioannis Pitas.
IEEE Transactions on Circuits and Systems for Video Technology (2013)

117 Citations

Minimum Class Variance Support Vector Machines

S. Zafeiriou;A. Tefas;I. Pitas.
IEEE Transactions on Image Processing (2007)

115 Citations

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