H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 61 Citations 18,168 415 World Ranking 1456 National Ranking 59

Research.com Recognitions

Awards & Achievements

2014 - Fellow of the Royal Society of Canada Academy of Science

2008 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to fundamental, applied and industrial problems in pattern recognition and neural networks.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

His primary scientific interests are in Artificial intelligence, Cluster analysis, Data mining, Pattern recognition and Machine learning. His Artificial intelligence research incorporates elements of Computer vision and Natural language processing. His biological study deals with issues like Algorithm, which deal with fields such as Data set, Consensus clustering and Control theory.

Mohamed S. Kamel has included themes like Wavelet, Wavelet transform and Radial basis function in his Data mining study. The concepts of his Pattern recognition study are interwoven with issues in Pixel, Feature, Speech processing and Biometrics. He combines subjects such as Variety and Pattern recognition with his study of Machine learning.

His most cited work include:

  • Survey on speech emotion recognition: Features, classification schemes, and databases (1074 citations)
  • Cost-sensitive boosting for classification of imbalanced data (919 citations)
  • CLASSIFICATION OF IMBALANCED DATA: A REVIEW (683 citations)

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

Mohamed S. Kamel mainly focuses on Artificial intelligence, Pattern recognition, Machine learning, Data mining and Cluster analysis. The Artificial intelligence study combines topics in areas such as Computer vision and Natural language processing. His Pattern recognition study frequently draws connections to adjacent fields such as Feature.

He combines topics linked to Training set with his work on Machine learning. Data mining and Fuzzy logic are commonly linked in his work. His study in Correlation clustering, Fuzzy clustering, CURE data clustering algorithm, Document clustering and Clustering high-dimensional data is done as part of Cluster analysis.

He most often published in these fields:

  • Artificial intelligence (61.47%)
  • Pattern recognition (26.32%)
  • Machine learning (17.11%)

What were the highlights of his more recent work (between 2011-2021)?

  • Artificial intelligence (61.47%)
  • Pattern recognition (26.32%)
  • Machine learning (17.11%)

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

Artificial intelligence, Pattern recognition, Machine learning, Data mining and Cluster analysis are his primary areas of study. His Artificial intelligence research integrates issues from Particle swarm optimization and Computer vision. His study focuses on the intersection of Pattern recognition and fields such as Feature with connections in the field of Feature selection.

His study in the fields of Bayesian network under the domain of Machine learning overlaps with other disciplines such as Novelty detection. His work deals with themes such as DBSCAN, Data modeling, Random projection and Euclidean distance, which intersect with Data mining. He works mostly in the field of Dimensionality reduction, limiting it down to topics relating to Principal component analysis and, in certain cases, Speech recognition.

Between 2011 and 2021, his most popular works were:

  • Efficient greedy feature selection for unsupervised learning (63 citations)
  • Kernelized Supervised Dictionary Learning (58 citations)
  • Vehicle localization in VANETs using data fusion and V2V communication (44 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

Mohamed S. Kamel mainly investigates Artificial intelligence, Pattern recognition, Sensor fusion, Data mining and Machine learning. His studies in Sparse approximation, K-SVD, Facial recognition system, Supervised learning and Kernel are all subfields of Artificial intelligence research. His Pattern recognition study integrates concerns from other disciplines, such as Feature, Speech recognition and Computer vision.

His study in Sensor fusion is interdisciplinary in nature, drawing from both Computer security, Real-time computing, Simulation and Service. His research integrates issues of Random projection, Data point, Greedy algorithm and Cluster analysis in his study of Data mining. His work carried out in the field of Machine learning brings together such families of science as Threat assessment, Data integration, Inference and Exploit.

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.

Top Publications

Survey on speech emotion recognition: Features, classification schemes, and databases

Moataz El Ayadi;Mohamed S. Kamel;Fakhri Karray.
Pattern Recognition (2011)

1658 Citations

Cost-sensitive boosting for classification of imbalanced data

Yanmin Sun;Mohamed S. Kamel;Andrew K. C. Wong;Yang Wang.
Pattern Recognition (2007)

1389 Citations

CLASSIFICATION OF IMBALANCED DATA: A REVIEW

Yanmin Sun;Andrew K. C. Wong;Mohamed S. Kamel.
International Journal of Pattern Recognition and Artificial Intelligence (2009)

1047 Citations

Image Analysis and Recognition

Aurélio Campilho;Mohamed S. Kamel.
Lecture Notes in Computer Science (2004)

905 Citations

A survey of palmprint recognition

Adams Kong;David Zhang;Mohamed Kamel.
Pattern Recognition (2009)

603 Citations

Efficient phrase-based document indexing for Web document clustering

K.M. Hammouda;M.S. Kamel.
IEEE Transactions on Knowledge and Data Engineering (2004)

478 Citations

Palmprint identification using feature-level fusion

Adams Kong;David Zhang;Mohamed Kamel.
Pattern Recognition (2006)

388 Citations

Extraction of binary character/graphics images from grayscale document images

Mohamed Kamel;Aiguo Zhao.
CVGIP: Graphical Models and Image Processing (1993)

325 Citations

An analysis of BioHashing and its variants

Adams Kong;King-Hong Cheung;David Zhang;Mohamed Kamel.
Pattern Recognition (2006)

312 Citations

Shape retrieval using triangle-area representation and dynamic space warping

Naif Alajlan;Ibrahim El Rube;Mohamed S. Kamel;George Freeman.
Pattern Recognition (2007)

308 Citations

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

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