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Feature shaping for linear SVM classifiers

George Forman, Martin Scholz, Shyamsundar Rajaram
2009 Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '09  
text classification machine learning, feature weighting, feature scaling, SVM Linear classifiers have been shown to be effective for many discrimination tasks.  ...  We demonstrate that this pre-processing is beneficial for linear SVM classifiers on a large benchmark of text classification tasks as well as UCI datasets.  ...  The goal is to help the classifier induction step by transforming raw feature values into a representation well suited for linear classifiers.  ... 
doi:10.1145/1557019.1557057 dblp:conf/kdd/FormanSR09 fatcat:gwt4nqloyjgstjblptjpqqcmtu

Comparison of the histogram of oriented gradient, GLCM, and shape feature extraction methods for breast cancer classification using SVM

Hanimatim Mu'jizah, Dian Candra Rini Novitasari
2021 Jurnal Teknologi dan Sistem Komputer  
The shape feature extraction-SVM using Linear kernel shows the best performance with an accuracy of 98.44 %, sensitivity of 100 %, and specificity of 97.50 %.  ...  It compares the performance of three features extraction methods used in SVM, namely Histogram of Oriented Gradient (HOG), GLCM, and shape feature extraction.  ...  Based on these results, shape feature extraction-SVM classification obtains the best results using the Linear kernel with 0.04 seconds for computational time.  ... 
doi:10.14710/jtsiskom.2021.14104 fatcat:ckfjgpy34zbsze4idcqxxg26mu

Detection of the Presence of Safety Helmets on Motorcyclists Using Active Appearance Models

Felipe Jose Aguiar Maia, Jose Everardo Bessa Maia, Thelmo Pontes de Araujo
2018 Journal of Intelligent Computing  
This adjustment is measured by differences between AAM shape and appearance parameter vectors, which become the feature vectors for four different classifiers.  ...  The degree of adjustment of a new image to the previously trained Active Appearance Model (AAM) acts as the decision criterion for detection.  ...  In terms of mean accuracy, the performance of SVM with non-linear polynomial kernel and MLP classifiers are practically the same, with a little advantage for the SVM with non-linear polynomial kernel classifier  ... 
doi:10.6025/jic/2018/9/4/157-165 fatcat:onx7qjugjna4pcpfjaj326yx3i

A Robust mRMR Based Pedestrian Detection Approach Using Shape Descriptor

Kaushal Kumar, Ritesh Mishra
2019 Traitement du signal  
In this paper, feature selector is used along with Histogram of Significant Gradients (HSG) descriptor and linear SVM classifier to enhance the detection accuracy and reduce the processing time.  ...  A comparative study has been done employing different classifiers and feature selectors and a system is proposed with better detection capability.  ...  SVM classifier with and without various feature selectors Classifier TP TN FP FN SVM Linear 560 1065 17 179 SVM Linear with mRMR 645 1044 38 94 SVM Linear with JMI 635 1048 34  ... 
doi:10.18280/ts.360110 fatcat:zukprn5lyvcuvofhnu6hzwmwe4

PERFORMANCE ANALYSIS OF FRUIT CROP FOR MULTICLASS SVM CLASSIFICATION

Shameem Fatima
2020 JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES  
The Experiments was carried out to find the best SVM kernel among linear, cubic and Gaussian for fruit categorization.  ...  It is measured by analyzing the different mention kernel selection on color and shape features. Two coding design method such as one-vs.-one and one-vs.  ...  /Model Kernel technique Dataset Features Accuracy 1 [XIX] Multi class SVM - - Color and Shape 92.22% 2 [XV] Multiclass SVM- Linear Fruit 360 Color ,Shape 98-100% 3 Proposed work  ... 
doi:10.26782/jmcms.2020.08.00015 fatcat:hzo554qzefhhzcprbnqsir3u4i

Face shape classification using Inception v3 [article]

Adonis Emmanuel Tio
2019 arXiv   pre-print
(LDA), support vector machines with linear kernel (SVM-LIN), support vector machines with radial basis function kernel (SVM-RBF), artificial neural networks or multilayer perceptron (MLP), and k-nearest  ...  Results show that training accuracy and overall accuracy ranges from 98.0% to 100% and from 84.4% to 84.8% for Inception v3 and from 50.6% to 73.0% and from 36.4% to 64.6% for the other classifiers depending  ...  Five classifiers were trained and tested using features obtained from 500 images: linear discriminant analysis (LDA), support vector machines with linear (SVM-LIN) and radial basis function kernels (SVM-RBF  ... 
arXiv:1911.07916v1 fatcat:5hhmq5izjvgmtlcn7i4nzekrou

Poetry Classification Using Support Vector Machines

Rang
2012 Journal of Computer Science  
We used tfidf for both classification experiments and the shape feature for the classification of poetry and non-poetry experiment alone.  ...  The capability of SVM through Radial Basic Function (RBF) and linear kernel function are implemented to classify pantun by theme, as well as poetry or non-poetry.  ...  In this case, meanings of poetry give better features for the SVM classifier. Table 5 .  ... 
doi:10.3844/jcssp.2012.1441.1446 fatcat:ogzqzt46pnfphkktftqyd6hwgq

People recognition and pose estimation in image sequences

C. Nakajima, M. Pontil, T. Poggio
2000 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium  
The person in the image is represented by a set of features based on color and shape information.  ...  Recognition is carried out through a hierarchy of biclass SVM classifiers that are separately trained to recognize people and estimate their poses.  ...  The core of the system is a multiclass classification problem which we have approached using two types of hierarchical SVM classifiers.  ... 
doi:10.1109/ijcnn.2000.860771 dblp:conf/ijcnn/NakajimaPP00 fatcat:7k67peaffbfwdahxn55gp56svy

Benign and Malignant Dermatoscopy Image Classification

T. Christy Bobby
2020 2020 Third International Conference on Advances in Electronics, Computers and Communications (ICAECC)  
Dermatologists use various techniques for diagnosing the malignant, in which the popular and reliable clinical method is dermatoscopy.  ...  Thus recently, image processing and machine learning algorithms have been applied for the accurate diagnoses of skin cancers from the dermatoscopic images.  ...  Using ReliefF algorithm, the non-linear SVM with polynomial kernel of order3 outperformed all other SVM classifiers with 90% accuracy, 91% sensitivity, 86% specificity, and 93% precision.  ... 
doi:10.1109/icaecc50550.2020.9339500 fatcat:r4zpogqlfneebne4bjkmskumfq

A Comparative Study of Feature Extraction Methods in Images Classification

Seyyid Ahmed Medjahed
2015 International Journal of Image Graphics and Signal Processing  
We analyze the models obtained by each feature extraction method under each classifier.  ...  However, in this paper, we present a comparison protocol of several feature extraction techniques under different classifiers.  ...  Shape Features Shape features are very used in the literature (in object recognition and shape description).  ... 
doi:10.5815/ijigsp.2015.03.03 fatcat:jwz3f4jtsffhjholmk74qik45y

Morphometric Analysis of Brain Structures for Improved Discrimination [chapter]

Li Shen, James Ford, Fillia Makedon, Yuhang Wang, Tilmann Steinberg, Song Ye, Andrew Saykin
2003 Lecture Notes in Computer Science  
Spherical harmonics technique and point distribution model are used for shape description.  ...  Classification is performed using linear discriminants and support vector machines with several feature selection approaches.  ...  We thank Martin Styner and Hany Farid for valuable discussions, and Laura Flashman for data preparation.  ... 
doi:10.1007/978-3-540-39903-2_63 fatcat:xdhgz4exnfhz3pz75t2fjxvg3i

Improving the Performance of Human Detection Technique using Cascaded Support Vector Machine

Raksha Tomar, Murlidhar Vishwakarma, Ravi Singh Pippal
2015 International Journal of Computer Applications  
The classification process define the pattern of feature for the process of detection, the process of features generates a bag of feature for the process of classification technique.  ...  The process of human detection is very complex due to variant feature of human such as color, texture and shape and size.  ...  training data by using linear SVM.  ... 
doi:10.5120/20531-2872 fatcat:5xbu5tfmxveuhhcpse4woge3ey

PLANT LEAF RECOGNITION SYSTEM USING KERNEL ENSEMBLE APPROACH

Phiros Mansur
2018 International journal of advances in signal and image sciences  
The classification is done by ensemble approach with different SVM kernels like Linear (SVM-L), Radial basis function (SVM-R), Polynomial (SVM-P) and Quadratic (SVM-Q).  ...  Finally, the outputs of each SVM classifier are fused to classify plant leaf images. The PLR system is carried on using Folio database that contains 640 leaf images captured from 32 species.  ...  Shape features for PLR is described in [2] using neural network. The moment invariant features are used as shape features to classify three plants.  ... 
doi:10.29284/ijasis.4.1.2018.30-36 fatcat:pd3mlgbbe5c27i7kw2uwnm2xuu

Two-Stage Traffic Sign Detection and Recognition Based on SVM and Convolutional Neural Networks

Ahmed Hechri, Abdellatif Mtibba
2019 IET Image Processing  
The first stage aims to detect and classify the detected traffic signs into circular and triangular shape using HOG features and linear support vector machines (SVMs).  ...  Furthermore, the average processing time demonstrates its suitability for real-time processing applications.  ...  After image filtering, circular and triangular shapes were classified by the linear SVM with HOG features.  ... 
doi:10.1049/iet-ipr.2019.0634 fatcat:4lxutq6rivfhlin7lhetvo6wqu

Robust facial expression classification using shape and appearance features

S L Happy, Aurobinda Routray
2015 2015 Eighth International Conference on Advances in Pattern Recognition (ICAPR)  
By using linear discriminant analysis, the dimensionality of the feature is reduced which is further classified by using the support vector machine (SVM).  ...  The use of small parts of face instead of the whole face for extracting features reduces the computational cost and prevents the over-fitting of the features for classification.  ...  Jeffery Cohn for providing the Cohn-Kanade database, and Dr. Michael J. Lyons for providing JAFFE database.  ... 
doi:10.1109/icapr.2015.7050661 dblp:conf/icapr/HappyR15 fatcat:63bacjoqq5ez5lj43dfvwvu3mu
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