[PDF] Top 20 Efficient Method for Video Summarization Using Support Vector Machine
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Efficient Method for Video Summarization Using Support Vector Machine
... Support vector machine (SVM) is a non-linear ...the method is to nonlinearly map the input data to some high dimensional space, where the data can be linearly separated, thus providing great ... See full document
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An Efficient Method to Get Improved Peak Signal to Noise Ratio (PSNR), Using Support Vector Machine
... through support vector machine is an excellent approach because it removes unwanted noise, by virtue of possessed the image ...denoising using Support Vector Machine with ... See full document
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Anomaly Detection using Support Vector Machine
... Abstract: Support vector machine are among the most well known supervised anomaly detection technique, which are very efficient in handling large and high dimensional ...powerful ... See full document
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Energy Benchmarking In A Portfolio Of Educational Buildings In Brazil Using Support Vector Machine And Data Envelopment Analysis
... of efficient DMUs, which makes the analysis more difficult, especially when it is intended to order the DMUs by ...Brazil, using SVM to predict energy consumption, and DEA for the efficiency analysis and ... See full document
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Efficient Seizure Classification using Multiclass Support Vector Machine with RFE
... description. Sets A and B have been acquired from surface EEG recordings of five healthy volunteers, with eyes open and closed, respectively. Signals in subsets C and D have been measured in seizure-free intervals, from ... See full document
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Efficient Cluster Based Classification in Big Data Analysis using Support Vector Machine
... for efficient environmental science has increased along with the rise of the information era and “big data across all field in ...analysis, Machine learning approach is an approach used for classification ... See full document
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Classification of power disturbances using multilevel support vector Machine
... wavelet-based support vector machine classifiers for power disturbance recognition and ...proposed method can reduce the quantity of extracted features of distorted signal without losing its ... See full document
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Comparison between Euclidean Distance Metric and SVM for CBIR using Level Set Features
... by using non-parametric (Euclidean distance) and a parametric (Support Vector Machine) classification method is presented for two standard ...and Support Vector ... See full document
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Insertion of Ontological Knowledge to Improve Automatic Summarization Extraction Methods
... by extraction can be grouped into three approaches: sta- tistical, enriched statistical and machine learning [5]. In this research work, we are interested especially in ma- chine learning approaches because the ... See full document
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AN EFFICIENT DETECTION OF STRUCTURAL SIMILARITY IN MAMMOGRAMS USING SUPPORT VECTOR MACHINE (SVM) CLASSIFIER
... Histogram modified filter and K-means clustering is applied prior to LBP based detection has been proposed in [13].The classification done with the help of Neural Network. The accuracy of this system for a set of 5 ... See full document
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A Method for Surface Reconstruction Based on Support Vector Machine
... a method for reconstruct surface based on Support Vector Machine (SVM) is ...simplification method is employed to simplify cloud points ...reconstruction method based on ... See full document
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An Efficient Email Spam Detection using Support Vector Machine
... 1. Support Vector Machine Learning Algorithm Support Vector Machine is used for classification and also for regression problems where the datasets are used to train the SVM to ... See full document
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Human Activity Recognition Using HOG Features
... of machine learning and computer vision. This paper presents a method to automatically identify human activity from input video stream using Histogram of Oriented Gradient features (HOG) and ... See full document
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Spatial Prediction of Landslides using Time Series Analysis and Support Vector Machine
... GA is a family of population-based search algorithms for optimization problems. They maintain a set of solutions known as population. In each generation, it generates a new population from the current population ... See full document
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Development of Mushroom Expert System Based on SVM Classifier and Naive Bayes Classifier
... The expert system [3] is a knowledge system which takes computer as a tool and makes use of the expertise and knowledge consequence to comprehend and solve the problem. It imitates the macroscopically inferential ... See full document
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Document Classification Using Support Vector Machine
... Text categorization (TC – also known as text classification, or topic spotting) is the task of automatically sorting a set of documents into categories (or classes, or topics) from a predefined set [13].The concept of ... See full document
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Advance Probabilistic Binary Decision Tree using SVM
... Support vector machine(SVM) has become one of the most widely used machine learning algorithm, mostly for classification[1]. SVM is classifiers which is originally designed for solving binary ... See full document
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A Survey on Intrusion Detection Systems and Classification Techniques
... A set of features that describes one case is called a vector. That is why the goal of SVM modelling is to find the optimal hyper plane that separates group of classes in a way that cases with one group of the ... See full document
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Improved Accuracy in Determining Elderly Nutritional Status Using Support Vector Machine Method
... Current method used to determine nutritional status of elderly is by measuring and categorizing with Body Mass Index (BMI) ...status using support vector machine (SVM) and data ... See full document
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Advanced Probabilistic Binary Decision Tree Using SVM for large class problem
... of Support Vector Machine here present Advanced Probabilistic Binary Decision Tree (APBDT) using Support Vector Machine (SVM) as an original approach to the multi-class ... See full document
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