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Haar-like features and classification SVM rates (accuracy)

Nao detection with a cascade of boosted weak classifier based on Haar-like features

Nao detection with a cascade of boosted weak classifier based on Haar-like features

... of features misclassified by the previous ...one Haar-like feature which best discriminates between the positive and negative ...threshold classification function that minimizes the number of ...

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Baseline Avatar Face Detection using an Extended Set of Haar-like Features

Baseline Avatar Face Detection using an Extended Set of Haar-like Features

... of Haar like features by extending the Viola Jones approach towards rapid object ...this Haar cascade on human and avatar faces. Accuracy rates of 79% on human and 74% on avatar faces ...

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Speech emotion classification using SVM and MLP on prosodic and voice quality features

Speech emotion classification using SVM and MLP on prosodic and voice quality features

... used SVM and NN, with 68 features related to pitch, energy, ZCR, power, and MFCC extracted from the Berlin database, to detect seven emotions including anger, happiness, fear, sadness, disgust, boredom, and ...

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Cumulant Features based Classification of Brain MR Images using ANN and LS SVM Algorithm

Cumulant Features based Classification of Brain MR Images using ANN and LS SVM Algorithm

... The acquiring procedure of brain magnetic resonance image is a non-invasive with low-risk to provide high quality brain images and produces detailed information for disease diagnosis and research. The MR images are the ...

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Multiclass Brain Tumor Classification using SVM

Multiclass Brain Tumor Classification using SVM

... 3. RESULTS AND DISCUSSIONS In present work a supervised method for the classification of MR imges in multiclass has been applied. As mentioned the method employs four stages: Preprocessing, feature extraction, ...

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ECG Image Classification in Real time based on the Haar-like Features and Artificial Neural Networks

ECG Image Classification in Real time based on the Haar-like Features and Artificial Neural Networks

... artificial multilayer perceptron type neural network. The iterative processof theneural networkendsby minimizingthe overall errororby reachingthe maximum number ofiteration After adjusting the connection weights between ...

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Haar-like-features for query-by-string word spotting

Haar-like-features for query-by-string word spotting

... In the literature, word spotting approaches have been applied to various scripts such as Latin, Arabic, Greek, etc. Word spotting approaches have been divided into different categories in multiple ways by document ...

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Detection of fake shallots using website-based haar-like features algorithm

Detection of fake shallots using website-based haar-like features algorithm

... The Ca scade Classifier stage is a n image classification process based on the number of features that ma tch a given filter a nd cla ssified whether it includes objects or not. When the compared image ...
Bag of Features Based Remote Sensing Image Classification Using RANSAC And SVM

Bag of Features Based Remote Sensing Image Classification Using RANSAC And SVM

... RANSAC, SVM, Bag of ...distinctive features, which are efficient in computation time and memory ...performance rates. Remote sensing image classification has become very important research ...

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Identifying Online Sexual Predators by SVM Classification with Lexical and Behavioral Features 1

Identifying Online Sexual Predators by SVM Classification with Lexical and Behavioral Features 1

... are like or how they behave. Rather, we cast a wide net of features and left it to our machine learning tools to identify which are predictive of ...

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CLASSIFICATION OF COPY MOVE FOREGERY AND NORMAL IMAGES BY ORB FEATURES AND SVM CLASSIFIER

CLASSIFICATION OF COPY MOVE FOREGERY AND NORMAL IMAGES BY ORB FEATURES AND SVM CLASSIFIER

... b) Image Splicing: This system is more forceful than modifying. Picture Spicing is a method that includes a composite of at least two pictures which are joined to make a phony picture. c) Copy-Move Attack: Copy-Move ...

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Human Eye Blink Detection using YCbCr Color Model, Haar-Like Features and Template Matching

Human Eye Blink Detection using YCbCr Color Model, Haar-Like Features and Template Matching

... has also been adjusted to achieve very high detection rates. A positive result from the second classifier triggers a third classifier, and so on Stages in the cascade are constructed by training classifiers using ...

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Vehicle Identification Based on Haar-Like Compression Feature

Vehicle Identification Based on Haar-Like Compression Feature

... traditional haar-like feature extraction algorithm is a method based on integral image to help extract image features with different feature ...many features extracted, there is redundant ...

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Informed Haar-like Features Improve Pedestrian Detection

Informed Haar-like Features Improve Pedestrian Detection

... multi-channel Haar-like features represent characteristic differences be- tween parts of the human body yet are robust against vari- ations in clothing or environmental ...rectangle features ...

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Features Selection Based ABC SVM and PSO SVM in Classification Problem

Features Selection Based ABC SVM and PSO SVM in Classification Problem

... the classification of data will use Support Vector Machine to produce an increase in average Precision, Recall and F measure, and Area Under Cover (AUC) values compared to the method the comparison is ...this ...

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Face recognition smart cane using haar-like features and eigenfaces

Face recognition smart cane using haar-like features and eigenfaces

... using Haar-Like Features can be used as a tool aid for blind to recognize the other person as long there is one face is captured on camera with average delay 3 ...

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Real time computation of Haar like features at generic angles for detection algorithms

Real time computation of Haar like features at generic angles for detection algorithms

... the features can fit the position and the sizes ...the features’ definition or implementation itself, it is an important source of errors during the detection phase or ...

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Cervical Vertebral Corner Detection using Haar-like Features and Modified Hough Forest

Cervical Vertebral Corner Detection using Haar-like Features and Modified Hough Forest

... radiographs. Haar-like features are computed using intensity and gradient image patches, each of which votes for possible corner position using a modified Hough forest regression ...

7

Real-time Detection of Vehicles Using the Haar-like Features and Artificial Neuron Networks

Real-time Detection of Vehicles Using the Haar-like Features and Artificial Neuron Networks

... Until now, many researchers have proposed vehicle detection algorithms. A trivial solution for vehicle detection is the exhaustive search of all possible positions in the processed image. But this solution remains ...

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Statistical Features and Traditional SA SVM Classification Algorithm for Crack Detection

Statistical Features and Traditional SA SVM Classification Algorithm for Crack Detection

... of features which can effectively determine the health state of the ...These features need to be sensitive enough to detect any discontinuity happens in the ...These features are directly affecting ...

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