Journal ArticleDOI
A new method of feature fusion and its application in image recognition
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TLDR
Experimental results on Concordia University CENPARMI database of handwritten Arabic numerals and Yale face database show that recognition rate is far higher than that of the algorithm adopting single feature or the existing fusion algorithm.About:Â
This article is published in Pattern Recognition.The article was published on 2005-12-01. It has received 469 citations till now. The article focuses on the topics: Feature (machine learning) & Feature vector.read more
Citations
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Journal ArticleDOI
A Review of Human Activity Recognition Methods
TL;DR: This work proposes a categorization of human activity methodologies and divides human activity classification methods into two large categories according to whether they use data from different modalities or not, and examines the requirements for an ideal human activity recognition dataset.
Journal ArticleDOI
Deep Feature Fusion for VHR Remote Sensing Scene Classification
TL;DR: The pretrained visual geometry group network (VGG-Net) model is proposed as deep feature extractors to extract informative features from the original VHR images to produce good informative features to describe the images scene with much lower dimension.
Journal ArticleDOI
Discriminant Correlation Analysis: Real-Time Feature Level Fusion for Multimodal Biometric Recognition
TL;DR: In this paper, a discriminant correlation analysis (DCA) is proposed for feature fusion by maximizing the pairwise correlations across the two feature sets and eliminating the between-class correlations and restricting the correlations to be within the classes.
Journal ArticleDOI
Detection and classification of citrus diseases in agriculture based on optimized weighted segmentation and feature selection
Muhammad Sharif,Muhammad Attique Khan,Muhammad Attique Khan,Zahid Iqbal,Muhammad Faisal Azam,M. Ikram Ullah Lali,Muhammad Younus Javed +6 more
TL;DR: The proposed hybrid method for detection and classification of diseases in citrus plants outperforms the existing methods and achieves 97% classification accuracy on citrus disease image gallery dataset, 89% on combined dataset and 90.4% on the authors' local dataset.
Journal ArticleDOI
A Survey of Decision Fusion and Feature Fusion Strategies for Pattern Classification
TL;DR: A novel framework has been proposed, combining both the concepts of decision fusion and feature fusion to increase the performance of classification, and experiments have been done to prove the robustness of combining feature fusion and decision fusion techniques.
References
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Journal ArticleDOI
Eigenfaces for recognition
Matthew Turk,Alex Pentland +1 more
TL;DR: A near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals, and that is easy to implement using a neural network architecture.
Book ChapterDOI
Relations Between Two Sets of Variates
TL;DR: The concept of correlation and regression may be applied not only to ordinary one-dimensional variates but also to variates of two or more dimensions as discussed by the authors, where the correlation of the horizontal components is ordinarily discussed, whereas the complex consisting of horizontal and vertical deviations may be even more interesting.
Journal ArticleDOI
Regularized Discriminant Analysis
TL;DR: Alternatives to the usual maximum likelihood estimates for the covariance matrices are proposed, characterized by two parameters, the values of which are customized to individual situations by jointly minimizing a sample-based estimate of future misclassification risk.
Journal ArticleDOI
Invariant image recognition by Zernike moments
Alireza Khotanzad,Y.H. Hong +1 more
TL;DR: A systematic reconstruction-based method for deciding the highest-order ZERNike moments required in a classification problem is developed and the superiority of Zernike moment features over regular moments and moment invariants was experimentally verified.
Book
Multivariate statistical analysis
TL;DR: In this article, the authors describe the properties and characterizations of parameters and their functions in multivariate normal distributions, and test hypotheses of mean vectors and covariance matrices and mean vectors discriminant analysis principal components canonical correlations factor analysis.