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Nizar Bouguila

Nizar Bouguila

D-Index & Metrics

Computer Science

D-Index
55
Citations
10474
World Ranking
4367
National Ranking
174

Overview

Nizar Bouguila is affiliated with Concordia University in Canada, focusing primarily on research intersecting computer science and engineering disciplines. Their work spans a substantial number of publications within the domain of artificial intelligence, computer vision and pattern recognition, and electrical and electronic engineering.

Their research efforts are significantly represented in several main fields of study: computer science, with a major emphasis on artificial intelligence, as well as engineering. Within these broad fields, Bouguila's contributions cover subfields such as artificial intelligence, computer vision and pattern recognition, electrical and electronic engineering, signal processing, and statistics and probability.

The topics central to their research include Bayesian methods and mixture models, advanced clustering algorithms, text and document classification technologies, topic modeling, image retrieval and classification techniques, face and expression recognition, and anomaly detection techniques and applications.

Nizar Bouguila has published in multiple recognized venues frequently, with seven publications each in IEEE Transactions on Neural Networks and Learning Systems, Sensors, Pattern Analysis and Applications, Applied Intelligence, and the Proceedings of the International Florida Artificial Intelligence Research Society Conference.

Recent notable papers authored by or with involvement of Bouguila include:

  • "On Short-Term Load Forecasting Using Machine Learning Techniques and a Novel Parallel Deep LSTM-CNN Approach" (2021, IEEE Access)
  • "Graph Neural Networks for Intelligent Transportation Systems: A Survey" (2023, IEEE Transactions on Intelligent Transportation Systems)
  • "BLOCK-DBSCAN: Fast clustering for large scale data" (2020, Pattern Recognition)
  • "Clustering Analysis via Deep Generative Models With Mixture Models" (2020, IEEE Transactions on Neural Networks and Learning Systems)
  • "A new workflow for detailed urban scale building energy modeling using spatial joining of attributes for archetype selection" (2021, Journal of Building Engineering)

Collaborations play a significant role in their scientific output, with frequent coauthors including Manar Amayri, Wentao Fan, Narges Manouchehri, Fatma Najar, and Muhammad Azam.

Best Publications

  • On Short-Term Load Forecasting Using Machine Learning Techniques and a Novel Parallel Deep LSTM-CNN Approach

    Behnam Farsi;Manar Amayri;Nizar Bouguila;Ursula Eicker

  • Unsupervised learning of a finite mixture model based on the Dirichlet distribution and its application

    N. Bouguila;D. Ziou;J. Vaillancourt

  • High-Dimensional Unsupervised Selection and Estimation of a Finite Generalized Dirichlet Mixture Model Based on Minimum Message Length

    N. Bouguila;D. Ziou

  • A Fast Clustering Algorithm based on pruning unnecessary distance computations in DBSCAN for High-Dimensional Data

    Yewang Chen;Yewang Chen;Shengyu Tang;Nizar Bouguila;Cheng Wang

  • A Hybrid Feature Extraction Selection Approach for High-Dimensional Non-Gaussian Data Clustering

    S. Boutemedjet;N. Bouguila;D. Ziou

  • Unsupervised selection of a finite Dirichlet mixture model: an MML-based approach

    N. Bouguila;D. Ziou

  • BLOCK-DBSCAN: Fast clustering for large scale data

    Yewang Chen;Lida Zhou;Nizar Bouguila;Cheng Wang

  • Variational Learning for Finite Dirichlet Mixture Models and Applications

    Wentao Fan;N. Bouguila;D. Ziou

  • Practical Bayesian estimation of a finite beta mixture through gibbs sampling and its applications

    Nizar Bouguila;Djemel Ziou;Ernest Monga

  • Finite general Gaussian mixture modeling and application to image and video foreground segmentation

    Mohand Saïd Allili;Nizar Bouguila;Djemel Ziou

  • A study of spam filtering using support vector machines

    Ola Amayri;Nizar Bouguila

  • Network Anomaly Intrusion Detection Using a Nonparametric Bayesian Approach and Feature Selection

    Wajdi Alhakami;Abdullah ALharbi;Sami Bourouis;Roobaea Alroobaea

  • Clustering of Count Data Using Generalized Dirichlet Multinomial Distributions

    N. Bouguila

  • A hybrid SEM algorithm for high-dimensional unsupervised learning using a finite generalized Dirichlet mixture

    N. Bouguila;D. Ziou

  • Count Data Modeling and Classification Using Finite Mixtures of Distributions

    Nizar Bouguila

  • Positive vectors clustering using inverted Dirichlet finite mixture models

    Taoufik Bdiri;Nizar Bouguila

  • Hybrid Generative/Discriminative Approaches for Proportional Data Modeling and Classification

    N. Bouguila

  • A Dirichlet Process Mixture of Generalized Dirichlet Distributions for Proportional Data Modeling

    N. Bouguila;D. Ziou

  • Bayesian learning of finite generalized Gaussian mixture models on images

    Tarek Elguebaly;Nizar Bouguila

  • A Robust Video Foreground Segmentation by Using Generalized Gaussian Mixture Modeling

    M.S. Allili;N. Bouguila;D. Ziou

  • Fast neighbor search by using revised k-d tree

    Yewang Chen;Lida Zhou;Yi Tang;Jai Puneet Singh

Frequent Co-Authors

Djemel Ziou
Djemel Ziou Université de Sherbrooke
A. Ben Hamza
A. Ben Hamza Concordia University
Safya Belghith
Safya Belghith National Engineering School of Tunis
Douglas L. Arnold
Douglas L. Arnold Montreal Neurological Institute and Hospital
Ursula Eicker
Ursula Eicker Concordia University
Ali Ghrayeb
Ali Ghrayeb Hamad bin Khalifa University
Reinaldo A. Valenzuela
Reinaldo A. Valenzuela Nokia (United States)
De-Shuang Huang
De-Shuang Huang Tongji University
Victor Hugo C. de Albuquerque
Victor Hugo C. de Albuquerque Universidade Federal do Ceará
Chadi Assi
Chadi Assi Concordia University

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