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Ear and face based multimodal recognition could fully utilize their connection relationship, and implement recognizing people without their cooperation because of earpsilas special physiological location and structure. In this paper a kernel-based feature fusion algorithm is presented and applied to multimodal recognition based on fusing ear and face. With the algorithm, the associated feature vectors...
Ear recognition has been proved to be a promising subject in biometrics authentication. The fusion of ear and face biometrics could fully utilize their connection relationship, and possess the merit of recognizing persons without their cooperation because of earpsilas special physiological structure and location. In this paper a feature fusion method based on KPCA is proposed and applied to multimodal...
In this paper, we combine two leveled RBF neural network technique with D-S evidence fusion theory, and present an algorithm of target recognition based on double mode intelligent fusion of infrared and radar. An effective recognizing strategy is developed. Simulation on the algorithm is carried out and the results illustrate that the algorithm is efficient and effective.
In this paper, an object recognition algorithm of ship noise is presented combined a new kind of information processing technology with pattern matching. The procedure of processing acoustic signal of human being's hearing is imitated to extract the auditory correlation spectrum (ARS) as feature in the algorithm. Then, a novel feature named as summation of auditory correlation spectrum (SARS) is defined...
In this paper, a kind of recognition algorithm based on feature fusion combined with D-S evidence theory would be provided. In the given algorithm, the feature set and fusion algorithm would be decided separately through analyzing the character of different features and defining a new type of feature as well as designing probability evaluation function. The simulating results illustrate that the algorithm...
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