Using Support Vector Machines for MiRNA Identification

To segment a image with strongly varying object sizes results generally in under-segmentation of small structures or over-segmentation of big ones, which consequences poor classification accuracies. A strategy to produce multiple segmentations of one image and classification with support vector machines (SVM) of this segmentation stack afterwards is shown.

X. CAO{{, J. CHEN*{, B. MATSUSHITA§, H. IMURA" and L. WANG{{ {Key Laboratory of Environment Change and Natural Disaster, Ministry of Education of China, College of Resource Science and Technology, Beijing Normal University, Beijing, 100875, China {Graduate School of Engineering, Nagoya University, Nagoya 464-8603, Japan §Graduate School of Life and Environmental Sciences, University of Tsukuba,...

EYE DETECTION USING DISCRIMINATORY FEATURES AND AN EFFICIENT SUPPORT VECTOR MACHINE

In this chapter, we discuss two possible ways of improving the performance of the SVM, using geometric methods. The first adapts the kernel by magnifying the Riemannian metric in the neighborhood of the boundary, thereby increasing separation between the classes. The second method is concerned with optimal location of the separating boundary, given that the distributions of data on either side ...

Klinkenberg permeability is an important parameter in tight gas reservoirs. There are conventional methods for determining it, but these methods depend on core permeability. Cores are few in number, but well logs are usually accessible for all wells and provide continuous information. In this regard, regression methods have been used to achieve reliable relations between log readings and Klinke...