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Published in 2022 at "Medical physics"
DOI: 10.1002/mp.16093
Abstract: BACKGROUND Deep artificial neural networks such as convolutional neural networks (CNNs) have been shown to be effective models for reducing noise in CT images while preserving anatomic details. A practical bottleneck for developing CNN-based denoising…
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Keywords:
based training;
training framework;
noise;
phantom based ... See more keywords
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Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3212924
Abstract: The purpose of this article is to address unsupervised domain adaptation (UDA) where a labeled source domain and an unlabeled target domain are given. Recent advanced UDA methods attempt to remove domain-specific properties by separating…
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Keywords:
heterogeneous heuristic;
domain adaptation;
framework heterogeneous;
domain ... See more keywords
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Published in 2022 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2022.3233226
Abstract: Neural chat translation (NCT) aims to translate a cross-lingual chat between speakers of different languages. Existing context-aware NMT models cannot achieve satisfactory performances due to the following inherent problems: 1) limited resources of annotated bilingual…
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Keywords:
chat translation;
training;
multi;
stage ... See more keywords
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Published in 2019 at "Journal of Functional Morphology and Kinesiology"
DOI: 10.3390/jfmk4020025
Abstract: Over the last decade, there has been considerable interest in the individualisation of athlete training, including the use of genetic information, alongside more advanced data capture and analysis techniques. Here, we explore the evidence for,…
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Keywords:
personalised training;
development personalised;
emerging technologies;
training ... See more keywords