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Over 100 million cargo containers that are declared empty on their manifests are transported globally each year. Human operators can confirm if each is truly empty by physical inspection or by examination of an X-ray image. However, the huge number transported means that confirmation is far from complete. Thus, empty containers offer an opportunity for criminals to smuggle contraband. We report an...
In machine learning, non-linear dimensionality reduction (NLDR) is commonly used to embed high-dimensional data into a low-dimensional space while preserving local object adjacencies. However, the majority of NLDR methods define object adjacencies using distance metrics that do not account for the quality of the features in the high-dimensional space. In this paper we present Boosted Spectral Embedding...
This paper presents an extension to the Rule-Based Similarity (RBS) model a novel rough set approach to the problem of learning a similarity relation from data. The original model, proposed in [1], applied the notion of Tversky's feature contrast model in a rough set framework to facilitate an accurate case-based classification. In the dynamic RBS model, a dynamic reducts technique is used to broaden...
The aim of this study is to compare several classifiers commonly used within the field of speech emotion recognition (SER) on the speech based detection of self-confidence. A standard acoustic feature set was computed, resulting in 170 features per one-minute speech sample (e.g. fundamental frequency, intensity, formants, MFCCs). In order to identify speech correlates of self-confidence, the lectures...
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