Support Vector Machines for Microscopic Medical Images Compression

Characterization of digital medical images utilizing support vector machines

BACKGROUND In this paper we discuss an efficient methodology for the image analysis and characterization of digital images containing skin lesions using Support Vector Machines and present the results of a preliminary study. METHODS The methodology is based on the support vector machines algorithm for data classification and it has been applied to the problem of the recognition of malignant m...

STAGE-DISCHARGE MODELING USING SUPPORT VECTOR MACHINES

Establishment of rating curves are often required by the hydrologists for flow estimates in the streams, rivers etc. Measurement of discharge in a river is a time-consuming, expensive, and difficult process and the conventional approach of regression analysis of stage-discharge relation does not provide encouraging results especially during the floods. P

Support Vector Machines et Classification d’ Images

Classification of Images Using Support Vector Machines

Support Vector Machines (SVMs) are a relatively new supervised classification technique to the land cover mapping community. They have their roots in Statistical Learning Theory and have gained prominence because they are robust, accurate and are effective even when using a small training sample. By their nature SVMs are essentially binary classifiers, however, they can be adopted to handle the...

One-Class Support Vector Machines for Aerial Images Segmentation

Interpretation of aerial images is an important task in various applications. Image segmentation can be viewed as the essential step for extracting information from aerial images. Among many developed segmentation methods, the technique of clustering has been extensively investigated and used. However, determining the number of clusters in an image is inherently a difficult problem, especially ...