Djemel Ziou spends much of his time researching Artificial intelligence, Pattern recognition, Mixture model, Image retrieval and Unsupervised learning. His studies in Artificial intelligence integrate themes in fields like Data mining, Aerial survey and Computer vision. His study in the field of Image segmentation is also linked to topics like Generalized Dirichlet distribution.
His Mixture model study incorporates themes from Data modeling, Algorithm, Segmentation and Bayesian probability. His Image retrieval research is multidisciplinary, incorporating elements of Multinomial distribution, Probabilistic logic and Information retrieval. The study incorporates disciplines such as Automatic summarization and Expectation–maximization algorithm in addition to Unsupervised learning.
Djemel Ziou mainly focuses on Artificial intelligence, Pattern recognition, Computer vision, Mixture model and Algorithm. His biological study deals with issues like Machine learning, which deal with fields such as Data mining. His Pattern recognition research incorporates elements of Latent Dirichlet allocation and Cluster analysis.
His work is connected to Pixel, Image quality, Image processing, Edge detection and Histogram, as a part of Computer vision. His Mixture model research incorporates themes from Automatic summarization, Statistical model, Model selection and Expectation–maximization algorithm. His Algorithm study combines topics from a wide range of disciplines, such as Image and Curvature.
His primary areas of investigation include Artificial intelligence, Pattern recognition, Computer vision, Mixture model and Cluster analysis. Much of his study explores Artificial intelligence relationship to Machine learning. The Pattern recognition study combines topics in areas such as Bag-of-words model in computer vision, Invariant and Robustness.
As a part of the same scientific family, Djemel Ziou mostly works in the field of Computer vision, focusing on Feature vector and, on occasion, Digital image, JPEG, Embedding, Steganography and Multinomial logistic regression. His Mixture model study integrates concerns from other disciplines, such as Compositional data, Mixing, Bounded function, Constant and Discriminative model. He combines subjects such as Roundness and Image retrieval with his study of Image quality.
His main research concerns Artificial intelligence, Computer vision, Cluster analysis, Pattern recognition and Mixture model. Many of his studies involve connections with topics such as Function and Artificial intelligence. His work deals with themes such as Head and Feature vector, which intersect with Computer vision.
His study explores the link between Cluster analysis and topics such as Simple random sample that cross with problems in Segmentation, Sampling design and Feature learning. His Pattern recognition research includes themes of Generalized normal distribution, JPEG and Steganalysis. His work carried out in the field of Mixture model brings together such families of science as Machine learning and Model selection.
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Image Quality Metrics: PSNR vs. SSIM
Alain Hore;Djemel Ziou.
international conference on pattern recognition (2010)
Edge Detection Techniques-An Overview
Djemel Ziou;Salvatore Tabbone.
Распознавание образов и анализ изображен / Pattern Recognition and Image Analysis: Advances in Mathematical Theory and Applications (1998)
A comparative analysis of image fusion methods
Zhijun Wang;D. Ziou;C. Armenakis;D. Li.
IEEE Transactions on Geoscience and Remote Sensing (2005)
Image Retrieval from the World Wide Web: Issues, Techniques, and Systems
M. L. Kherfi;D. Ziou;A. Bernardi.
ACM Computing Surveys (2004)
Unsupervised learning of a finite mixture model based on the Dirichlet distribution and its application
N. Bouguila;D. Ziou;J. Vaillancourt.
IEEE Transactions on Image Processing (2004)
High-Dimensional Unsupervised Selection and Estimation of a Finite Generalized Dirichlet Mixture Model Based on Minimum Message Length
N. Bouguila;D. Ziou.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)
A Hybrid Feature Extraction Selection Approach for High-Dimensional Non-Gaussian Data Clustering
S. Boutemedjet;N. Bouguila;D. Ziou.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)
Unsupervised selection of a finite Dirichlet mixture model: an MML-based approach
N. Bouguila;D. Ziou.
IEEE Transactions on Knowledge and Data Engineering (2006)
Finite general Gaussian mixture modeling and application to image and video foreground segmentation
Mohand Saïd Allili;Nizar Bouguila;Djemel Ziou.
Journal of Electronic Imaging (2008)
Depth from Defocus Estimation in Spatial Domain
Djemel Ziou;Francois Deschenes.
Computer Vision and Image Understanding (2001)
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