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Face Recognition using PCA &LDA Algorithm

implement a face recognition method, using PCA&LDA Algorithm and compare these both algorithms with respect to time, memory and accuracy. Face;

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PCA-AdaBoost-LDA Face Recognition Algorithm

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Image Classification of Single Layered Cloud Types

, a new cloud image can be classified by comparing it with the specified image space using the PCA algorithm. Weather forecasting applications;

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Face Recognition

control systems. Topics discussed in this compilation include two-dimensional principal component analysis algorithms for face recognition;

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Face Detection and Recognition

, face recognition using evolutionary algorithms, and face recognition in frequency domain Discusses methods for the localization of face;

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Face Detection and Recognition

, face recognition using evolutionary algorithms, and face recognition in frequency domain Discusses methods for the localization of face;

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Facial Expression Recognition

dimensionality of mean features from Gabor filters is further reduced by using a kernel PCA technique with polynomial kernels. The kernel PCA technique;

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Nonlinear Principal Component Analysis and Its Applications

any types of measurement levels by using nonlinear PCA. Sparseness and joint dimension reduction and clustering for nonlinear data, the;

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Deep Learning with Applications Using Python

Explore deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and;

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Pattern Recognition and Computational Intelligence Techniques Using Matlab

pattern recognition and the computational intelligence using Matlab; Includes mixtures of theory, math, and algorithms, letting readers;

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Perspectives on Pattern Recognition

; construction damage assessment based on pattern recognition; Haken's pattern recognition algorithm as applied in engineering sciences; active contours;

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Principal Component Analysis Networks and Algorithms

algorithms and their extensions and generalizations, e.g., dual purpose, coupled PCA, GED, neural based SVD algorithms, etc. It also discusses;

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Principal Component Analysis

observations into set of values of linearly uncorrelated variables called principal components. This book elucidates the uses of PCA in distinct fields;

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Ethiopian face Recognition System Across Ages

shows that face recognition system designed using Fisher Linear Discriminant analysis (FLD) demonstrates the best accuracy of 83%. However, the;

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Face, Expression, and Iris Recognition Using Learning-based Approaches

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Face Recognition using Vector Quantization

This book presents a novel approach for Face Recognition using 'Vector Quantization'. Face Recognition is one of the popular biometric;

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Glassy Nuclei in Amorphous Ice

-density amorphous ice (LDA), supporting water's liquid-liquid transition scenarios. Pressure-dependent crystallisation experiments of differently;

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Image Recognition and Restoration

sensitivity to estimates are the objectives to be resolved in this book using iterative algorithms. The first of the algorithms addresses the;

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Practical Guide to SAP Profit Center Accounting

This book offers a comprehensive introduction to SAP ERP Profit Center Accounting (PCA) for both classic general ledger (GL) and the new GL;

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The The Computer Vision Workshop

understand image content Use contours for shape analysis, object detection, and recognition Track objects in videos using a variety of trackers;

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Advances in Independent Component Analysis and Learning Machines

probabilistic model for PCA and ICA Optimization methods for matrix decompositions Insights into the FastICA algorithm

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Face Recognition Using Colour Statistics

In this book, a new high performance face recognition system based on matching the colour pixel statistics is introduced. A pre-processing;

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Kernel Learning Algorithms for Face Recognition

Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced;

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Human Emotion Recognition from Face Images

This book discusses human emotion recognition from face images using different modalities, highlighting key topics in facial expression;

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Human Emotion Recognition from Face Images

This book discusses human emotion recognition from face images using different modalities, highlighting key topics in facial expression;

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Hands-On Deep Learning with R

Deepnet Key Features Understand deep learning algorithms and architectures using R and determine which algorithm is best suited for a specific;

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Face Recognition

Face Recognition: Cognitive and Computational Processes critically discusses current research in face recognition, leading to an original;

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