Semi-supervised clustering allows a user to specify available prior knowledge about the data to improve the clustering performance. A common way to express this information is in ...
We present a semi-Markov model for recognizing scene text that integrates character and word segmentation with recognition. Using wavelet features, it requires only approximate lo...
Allen R. Hanson, Erik G. Learned-Miller, Jerod J. ...
We propose a feature selection method that constructs each new feature by analysis of tight error clusters. This is a greedy, time-efficient forward selection algorithm that itera...
The National Library of Medicine has been developing CervigramFinder, a Web-accessible prototype content-based image retrieval (CBIR) system for cervical cancer research, to retri...
George R. Thoma, Jose Jeronimo, L. Rodney Long, Sa...
Processing of stereo images has become more and more important in recent years because of the availability of various stereo displaying devices. In particular, stabilizing of ster...
Kai Ki Lee, Kin-hong Wong, Man Kin Leung, Michael ...
Double JPEG compression detection is of significance in digital forensics. We propose an effective machine learning based scheme to distinguish between double and single JPEG comp...
This paper addresses the issue of counterfeit iris detection, which is a liveness detection problem in biometrics. Fake iris mentioned here refers to iris wearing color contact le...
We present a hierarchical feature fusion model for image classification that is constructed by an evolutionary learning algorithm. The model has the ability to combine local patch...
Fabien Scalzo, George Bebis, Mircea Nicolescu, Lea...
Speaker independent feature extraction is a critical problem in speech recognition. Oriented principal component analysis (OPCA) is a potential solution that can find a subspace r...
This paper presents methods for collecting and analyzing physiological and biomechanical data during recreational runs in order to classify an athlete's perceived fatigue sta...