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AICCSA
2005
IEEE
129views Hardware» more  AICCSA 2005»
13 years 9 months ago
Enhanced visual evaluation of feature extractors for image mining
Plus BROWSE SEARCH IEEE XPLORE GUIDE SUPPORT View TOC Enhanced visual evaluation of feature extractors for image mining Rodrigues, J.F., Jr. Traina, A.J.M. Traina, C., Jr. Comput. ...
José Fernando Rodrigues Jr., Agma J. M. Tra...
CRV
2007
IEEE
137views Robotics» more  CRV 2007»
14 years 1 months ago
Quantitative Evaluation of Feature Extractors for Visual SLAM
We present a performance evaluation framework for visual feature extraction and matching in the visual simultaneous localization and mapping (SLAM) context. Although feature extra...
Jonathan Klippenstein, Hong Zhang
SIBGRAPI
2003
IEEE
14 years 21 days ago
Using Efficient Visual Exploration Techniques to Evaluate Features for Content-Based Image Retrieval
This paper presents a novel visual approach to evaluate, in a fast and effective way, the development of new image feature extraction techniques concerning content-based image ret...
José Fernando Rodrigues Jr., César A...
ICDM
2008
IEEE
113views Data Mining» more  ICDM 2008»
14 years 1 months ago
Text Mining in Radiology Reports
Medical text mining has gained increasing interest in recent years. Radiology reports contain rich information describing radiologist’s observations on the patient’s medical c...
Tianxia Gong, Chew Lim Tan, Tze-Yun Leong, Cheng K...
CBMS
2009
IEEE
13 years 10 months ago
A medical image retrieval framework in correlation enhanced visual concept feature space
This paper presents a medical image retrieval framework that uses visual concepts in a feature space employing statistical models built using a probabilistic multi-class support v...
Md. Mahmudur Rahman, Sameer Antani, George R. Thom...