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Extractive text or speech summarization endeavors to select representative sentences from a source document and assemble them into a concise summary, so as to help people to browse and assimilate the main theme of the document efficiently. The recent past has seen a surge of interest in developing deep learning- or deep neural network-based supervised methods for extractive text summarization. This...
With the aim to improve the performance of feature matching, we present an unsupervised approach for adaptive description selection in the space of homographies. Inspired by the observation that the homographies of correct feature correspondences vary smoothly along the spatial domain, our approach stands on the unsupervised nature of feature matching, and can choose a good descriptor locally for...
Vehicle classification and counting play an important role in the intelligent transportation system, as they may serve to improve traffic congestion and safety problems. Therefore, this study has developed a real-time and vision-based vehicle classification and counting system. This will involve establishing Time-Spatial Images (TSI) from input video, removing the shadow portions in TSI through the...
We propose a heterogeneous information network mining algorithm: feature-enhanced Rank Class (F-Rank Class). F-Rank Class extends Rank Class to a unified classification framework that can be applied to binary or multiclass classification of unimodal or multimodal data. We experimented on a multimodal document dataset, 2008/9 Wikipedia Selection for Schools. For unimodal classification, F-Rank Class...
This paper proposes a rear vision camera-based vehicle detection system which could detect if any rear vehicle exists in ego lane and if any vehicles in adjacent lanes are overtaking. The source image is firstly applied with distortion calibration which helps the following Hough transform to detect the existence of lane lines. The rear vehicle in ego lane is detected by a combination of feature-based...
Gender recognition for interactive functions becomes essential topic in terms of service robotics applications. Ensemble learning which combines multiple classifiers prediction is now an active area of research in Machine Learning and Pattern Recognition. We propose an ensemble learning to facilitate gender classification. The features which we use are raw data (image pixels as input), Local binary...
This paper investigates lexical stress detection for Chinese learners of English, where a combined differential acoustic feature is developed to represent the lexical stress of polysyllabic words in continuous speech. The use of frame-averaged feature and the contextual information intra-word can be input to the classifiers without normalization. The word-based stress detection method proposed in...
In order to extract the significant edges of the medical image without the interference of the internal noise and the external noise, a new medical image edge extraction algorithm is proposed. We use the information measure to remove the internal noise. According to the characteristics of wavelet transform and our requirements, we design a new quadratic B spline wavelet to discriminate the external...
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