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Shlomo Dubnov
Capturing long-term statistics of signals and time series is important for modeling recurrent phenomena, especially when such recurrences are a-periodic and can be characterized by the approximate repetition of variable length motifs, such as patterns in...
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Femke M. Janssen, Katja K. H. Aben, Berdine L. Heesterman, Quirinus J. M. Voorham, Paul A. Seegers and Arturo Moncada-Torres
Machine learning (ML) models have proven to be an attractive alternative to traditional statistical methods in oncology. However, they are often regarded as black boxes, hindering their adoption for answering real-life clinical questions. In this paper, ...
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Olatunji Akinola, Olaide N. Oyelade and Absalom E. Ezugwu
In the past decade, the extraction of valuable information from online biomedical datasets has exponentially increased due to the evolution of data processing devices and the utilization of machine learning capabilities to find useful information in thes...
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Wenjing Yang, Liejun Wang, Shuli Cheng, Yongming Li and Anyu Du
Recently, deep learning to hash has extensively been applied to image retrieval, due to its low storage cost and fast query speed. However, there is a defect of insufficiency and imbalance when existing hashing methods utilize the convolutional neural ne...
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Graham Spinks and Marie-Francine Moens
This paper proposes a novel technique for representing templates and instances of concept classes. A template representation refers to the generic representation that captures the characteristics of an entire class. The proposed technique uses end-to-end...
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Sara Sekkate, Mohammed Khalil, Abdellah Adib and Sofia Ben Jebara
Because one of the key issues in improving the performance of Speech Emotion Recognition (SER) systems is the choice of an effective feature representation, most of the research has focused on developing a feature level fusion using a large set of featur...
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