Abstract 3D object recognition and pattern recognition are active and fast-growing research
areas in the field of computer vision. It is mandatory to define the pattern class, feature …

During the last two decades, a substantial amount of research efforts has been intended for
support vector machine at the application of various data mining tasks. Data Mining is a …

The aim of this paper is to develop a hybrid model of a powerful Convolutional Neural
Networks (CNN) and Support Vector Machine (SVM) for recognition of handwritten digit from …

The knowledge discovery process is as old as Homo sapiens. Until some time ago this
process was solely based on the 'natural personal'computer provided by Mother Nature …

The aim of this study is to establish a hybrid model for epileptic seizure detection with
genetic algorithm (GA) and particle swarm optimization (PSO) to determine the optimum …

Support Vector Machines (SVMs) have been one of the most successful machine learning
techniques for the past decade. For anomaly detection, also a semi-supervised variant, the …

A comprehensive introduction to Support Vector Machines and related kernel methods. In
the 1990s, a new type of learning algorithm was developed, based on results from statistical …

This paper addresses the problem of the classification of hyperspectral remote sensing
images by support vector machines (SVMs). First, we propose a theoretical discussion and …

Preoperative differentiation of complicated and uncomplicated appendicitis is challenging.
The research goal was to construct a new intelligent diagnostic rule that is accurate, fast …

We assess the applicability of several popular learning methods for the problem of
recognizing generic visual categories with invariance to pose, lighting, and surrounding …