Recognition of complex human behaviors in pool environment using foreground silhouette
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
Integrating complementary features with a confidence measure for speaker identification
ISCSLP'06 Proceedings of the 5th international conference on Chinese Spoken Language Processing
Adaptive neural complementary sliding-mode control via functional-linked wavelet neural network
Engineering Applications of Artificial Intelligence
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By exploiting the specialist capabilities of each classifier, a combined classifier may yield results which would not be possible with a single classifier. In this paper, we propose to combine the fingerprint and speaker verification decisions using a functional link network. This is to circumvent the nontrivial trial-and-error and iterative training effort as seen in backpropagation neural networks which cannot guarantee global optimal solutions. In many data fusion applications, as individual classifiers to be combined would have attained a certain level of classification accuracy, the proposed functional link network can be used to combine these classifiers by taking their outputs as the inputs to the network. The proposed network is first applied to a pattern recognition problem to illustrate its approximation capability. The network is then used to combine the fingerprint and speaker verification decisions with much improved receiver operating characteristics performance as compared to several decision fusion methods from the literature.