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Spectra intrinsically possess domain knowledge, making possible a domain-based feature selection model. The random subspace method, in combination with domain-knowledge-based feature sets, leads to improved classification accuracies in real-life biomedical problems. Using such feature sets allows for an efficient reduction of dimensionality, while preserving interpretability of classification outcomes,...
In this paper, a novel hybrid kernel machine ensemble is proposed for abnormal ECG beat detection to facilitate long-term monitoring of heart patients. A binary SVM is trained using ECG beats from different patients to adapt to the reference values based on the general patient population. A one-class SVM is trained using only normal ECG beats from a specific patient to adapt to the specific reference...
In this paper we study the application of user-dependent score fusion to multilevel speaker recognition. After reviewing related works in multimodal biometric authentication, a new score fusion technique is described. The method is based on a form of Bayesian adaptation to derive the personalized fusion functions from prior user-independent data. Experimental results are reported using the MIT Lincoln...
In this paper, we present biometric person recognition experiments in a real-world car environment using speech, face, and driving signals. We have performed experiments on a subset of the in-car corpus collected at the Nagoya University, Japan. We have used Mel-frequency cepstral coefficients (MFCC) for speaker recognition. For face recognition, we have reduced the feature dimension of each face...
After deploying a classifier in production it is essential to support its lifecycle. This paper describes the application of an ensemble of classifiers to support two stages of the lifecycle of an on-line classifier used to underwrite life insurance applications: the monitoring of its decisions quality and the updating of the production classifier over time. All combinations of five classification...
The RGB colour space is prominent as a colour representation and display scheme, although a number of other colour spaces have been developed over the years each with its own advantages and shortcomings with regard to its usefulness for colour/texture recognition. However, the recent advent of multiple classifier systems provides the unique opportunity to exploit the diverse information encapsulated...
In this paper we propose an innovative combination strategy for a system using video and audio stream of a news video to automatically segment it into stories. In our approach, the segmentation is performed in two steps: first, shots are classified by combining three different anchor shot detection algorithms using video information only. Then, the shot classification is improved by using a novel...
Face recognition systems often use different images of a subject for training and enrollment. Typically, one may use LDA using all the image samples or train a nearest neighbor classifier for each (separate) set of images. The latter can require that information about lighting or expression about each testing point be available. In this paper, we propose usage of different images in a multiple classifier...
Obtaining ground truth for hyperspectral data is an expensive task. In addition, a number of factors cause the spectral signatures of the same class to vary with location and/or time. Therefore, adapting a classifier designed from available labeled data to classify new hyperspectral images is difficult, but invaluable to the remote sensing community. In this paper, we use the Binary Hierarchical Classifier...
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