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Transformer models in biomedicine [PDF]
BMC Medical Informatics and Decision MakingDeep neural networks (DNN) have fundamentally revolutionized the artificial intelligence (AI) field. The transformer model is a type of DNN that was originally used for the natural language processing tasks and has since gained more and more attention ...
Sumit Madan +5 more
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Improving neural machine translation with POS-tag features for low-resource language pairs
Heliyon, 2022 Integrating linguistic features has been widely utilized in statistical machine translation (SMT) systems, resulting in improved translation quality. However, for low-resource languages such as Thai and Myanmar, the integration of linguistic features in ...
Zar Zar Hlaing +3 more
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Unraveling learning characteristics of transformer models for molecular design. [PDF]
Patterns (N Y)Roth JP, Bajorath J.
europepmc +2 more sources
Applied Sciences, 2023 In this paper, we analyzed the performance of different transformer models for regret and hope speech detection on two novel datasets. For the regret detection task, we compared the averaged macro-scores of the transformer models to the previous state-of-
Grigori Sidorov +3 more
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Improving Transformer-Based Neural Machine Translation with Prior Alignments
Complexity, 2021 Transformer is a neural machine translation model which revolutionizes machine translation. Compared with traditional statistical machine translation models and other neural machine translation models, the recently proposed transformer model radically ...
Thien Nguyen +3 more
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STHarDNet: Swin Transformer with HarDNet for MRI Segmentation
Applied Sciences, 2022 In magnetic resonance imaging (MRI) segmentation, conventional approaches utilize U-Net models with encoder–decoder structures, segmentation models using vision transformers, or models that combine a vision transformer with an encoder–decoder model ...
Yeonghyeon Gu +2 more
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Multi-Transformer: A New Neural Network-Based Architecture for Forecasting S&P Volatility
Mathematics, 2021 Events such as the Financial Crisis of 2007–2008 or the COVID-19 pandemic caused significant losses to banks and insurance entities. They also demonstrated the importance of using accurate equity risk models and having a risk management function able to ...
Eduardo Ramos-Pérez +2 more
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Low‐latency transformer model for streaming automatic speech recognition
Electronics Letters, 2022 Transformer models have made great progress in automatic speech recognition. However, it is challenging for streaming transformer models to make trade‐off between output latency and recognition accuracy.
Haoran Miao +2 more
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A Taxonomy of Model Transformation [PDF]
Electronic Notes in Theoretical Computer Science, 2006 AbstractThis article proposes a taxonomy of model transformation, based on the discussions of a working group on model transformation of the Dagstuhl seminar on Language Engineering for Model-Driven Software Development. This taxonomy can be used, among others, to help developers in deciding which model transformation language or tool is best suited to
Tom Mens, Pieter Van Gorp
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Model transformations with Tom [PDF]
Proceedings of the Twelfth Workshop on Language Descriptions, Tools, and Applications, 2012 Model Driven Engineering (MDE) advocates the use of Model Transformations (MT) in order to automate repetitive development tasks. Many different model transformation languages have been proposed with a significant tool development cost as common language elements like expressions, statements, ...
Bach, Jean-Christophe +3 more
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