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In this paper, a method of Attribute Reduction Based on Discernibility Matrix and a proximal support vector machine (psvm) is integrated and used to implement a classification of digitized mammograms. The Attribute Reduction Algorithm is used to reduce useless and interfering attributes of medical images, and the proximal support vector machine that runs faster, and is easy to implement, is used to...
Localizing license plate in an image enables vehicle detection and identification. Processing at high-definition (HD) image allows a better access of visual information but also enhances the necessity of multi-resolution analysis because license plates may appear in various sizes and shapes. A great computational burden is accompanied by processing the great number of candidate windows during multi-resolution...
Knowledge element relation extraction is to find predefined relations between pairs of knowledge elements from text documents. As a novel form for organization and management of knowledge resources, knowledge element relation can be utilized to establish knowledge navigation system, knowledge retrieval system and collaborative knowledge construction system. In this paper, we employ conditional random...
A novel approach for walking people detection is proposed in this paper, which is inspired by the idea of gait energy image (GEI). Unlike most of common human detection methods where usually a trained detector scans a single image and then generates a detection result, the proposed method detects people on a sequence of silhouettes which contain both appearance characteristics and motion characteristics...
Use of semantic content is one of the important tasks in image analysis, which needs to be addressed for improving image retrieval effectiveness. We present a method to assign multiple keywords to image using SVMs. Images are divided into three-level regions called global image, semi-global images and sub-images. For each of them, color, texture and edge features are extracted. Then, the trained SVMs...
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