Identification and mapping of the significant alterations are the main objectives of the exploration geochemical surveys. The field study is time-consuming and costly to produce the classified maps. Therefore, the processing of remotely sensed data, which provide timely and multi-band (multi-layer) data, can be substituted for the field study. In this study, the ASTER imagery is used for altera...

Considerable efforts have been devoted to the implementation of efficient optimization method for solving the Support Vector Machine dual problem. This document proposes an historical perspective and and in depth review of the algorithmic and computational issues associated with this problem.

Support Vector Machine (SVM) is one of the most popular classifiers in pattern recognition, which aims to find a hyperplane that can separate two classes of samples with the maximal margin. As a result, traditional SVM usually more focuses on the scatter between classes, but neglects the different data distributions within classes which are also vital for an optimal classifier in different real...

The motivation of this work is customizing 3D models for fabrication. It is desirable to update the visualization of the model’s problematic areas in real time during editing, but often these analysis algorithms are very time consuming. We investigate creating a fast update algorithm for per-vertex model fragility using machine learning. We propose and analyze a new feature vector formulation a...

Support vector machine has been explored and many applications found within various research areas and application domains. Many support vector machine techniques have been specifically developed for certain application domains. This paper is an attempt to provide an overview on applications of support vector machines within the oil refineries to the professionals inside oil refineries, researc...

Maritime domain awareness is critical for protecting sea lanes, ports, harbors, offshore structures and critical infrastructures against common threats and illegal activities. Limited surveillance resources constrain maritime domain awareness and compromise full security coverage at all times. This situation calls for innovative intelligent systems for interactive situation analysis to assist m...

This work presents a recognition system for epileptiform abnormalities based on electroencephalogram (EEG) analysis. The proposed system combines a Support Vector Machine classifier automatically trained by an implementation of machine learning approach known as Bag of Words.

In this paper, we introduce an approach to improve the recognition performance of a Hidden Markov Model (HMM) based monophone recognizer using Support Vector Machines (SVMs). We developed and examined a method for re-scoring the HMM recognizer hypotheses by SVMs in a phoneme recognition framework. Compared to a stand-alone HMM system, an improvement of 9.2% was reached on the TIMIT database and...