Results 141 to 150 of about 238,882 (174)

Modelling C-arm fluoroscopy and operating table kinematics via machine learning. [PDF]

Front Robot AI
Jaheen F, Gutta V, Fallavollita P.
europepmc   +1 more source

A dataset for translating local Bangla (Sylheti) dialects into standard Bangla. [PDF]

Data Brief
Prama TT, Oni MK.
europepmc   +1 more source

Translation approaches to support systemic anti-cancer therapy consent for individuals with limited English proficiency. [PDF]

Support Care Cancer
Hibbs SP, Nizam R, Tanzim U, Aiken L, Habib S, Hodgson S, Williams J, Januszewski A, Hantel A, Uddin MS, Isaacs T, Bajaj B, Cockburn O, Islam A, Pratt G, Federici FM.   +15 more
europepmc   +1 more source

Editorial: Brain-Computer Interfaces (BCIs) for daily activities: innovations in EEG signal analysis and machine learning approaches. [PDF]

Front Hum Neurosci
Al-Bander B.
europepmc   +1 more source

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Multilingual Neural Machine Translation

Proceedings of the 28th International Conference on Computational Linguistics: Tutorial Abstracts, 2020
The advent of neural machine translation (NMT) has opened up exciting research in building multilingual translation systems i.e. translation models that can handle more than one language pair. Many advances have been made which have enabled (1) improving translation for low-resource languages via transfer learning from high resource languages; and (2 ...
Raj Dabre, Chenhui Chu, Anoop Kunchukuttan   +2 more
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Neural machine translation and human translation

Babel. Revue internationale de la traduction / International Journal of Translation, 2023
Abstract By comparing the Chinese, English and French versions of “Exhortations of Learning” and “On Building a Human Community with a Shared Future,” translated by human translators and the neural machine translation systems respectively, this essay finds out that human translators have addressed the political and ideological factors more tactfully ...
Anfeng Sheng, Yankun Kong
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Neural Machine Translation

2019
The emergence of neural machine translation (NMT) has revolutionized the filed of machine translation. In the first section, we introduce the fundamental of NMT models. Then we study the advantages of NMT over traditional statistical machine translations (SMT), some of its existing challenges and recent research efforts.
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Neural Machine Translation with Deep Attention

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
Deepening neural models has been proven very successful in improving the model's capacity when solving complex learning tasks, such as the machine translation task. Previous efforts on deep neural machine translation mainly focus on the encoder and the decoder, while little on the attention mechanism.
Biao Zhang, Deyi Xiong, Jinsong Su
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Integrative oncology: Addressing the global challenges of cancer prevention and treatment

Ca-A Cancer Journal for Clinicians, 2022
Jun J Mao,, Msce, Lorenzo Cohen, Karen M Mustian   +2 more
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