Enhanced Performance of Multimodal Biometric Systems by Confidence Estimation
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In this paper, we propose a new approach for the automatic audio-based temporal alignment with confidence estimation of audio-visual data, recorded by different cameras, camcorders or mobile phones during social events. All recorded data is temporally alig ...
In this paper, we propose a new approach for the automatic audio-based out-of-scene detection of audio-visual data, recorded by different cameras, camcorders or mobile phones during social events. All recorded data is clustered to out-of-scene and in-scene ...
This chapter introduces a discriminative method for detecting and spotting keywords in spoken utterances. Given a word represented as a sequence of phonemes and a spoken utterance, the keyword spotter predicts the best time span of the phoneme sequence in ...
In this work we evaluate the impact of automated preprocessing of MR brain images on the prediction performance of a SVM AD classifier.Using a reference data set of 82 healthy controls and 82 individuals affected by AD we estimate the expected prediction a ...
In this paper, we propose a new approach for the automatic audio-based out-of-scene detection of audio-visual data, recorded by different cameras, camcorders or mobile phones during social events. All recorded data is clustered to out-of-scene and in-scene ...
In this paper, we propose a new approach for the automatic audio-based temporal alignment with confidence estimation of audio-visual data, recorded by different cameras, camcorders or mobile phones during social events. All recorded data is temporally alig ...