English Translation Software Accuracy Correction Based on Machine Learning Technology

Author:

Guo Shangying

Publisher

Springer International Publishing

Reference12 articles.

1. Simon, R., Erven, R., Steven, D.: Hybrid-DBT: hardware/software dynamic binary translation targeting VLIW. IEEE Trans. Comput.-Aided Des. Integrated Circ. Syst. 99(PP), 1 (2018)

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3. Matsuba, S., Tabuchi, H., Ohsugi, H., et al.: Accuracy of ultra-wide-field fundus ophthalmoscopy-assisted deep learning, a machine-learning technology, for detecting age-related macular degeneration. Int. Ophthalmol. 35(4), 598–605 (2018)

4. Birkenbeuel, J., Joyce, H., Sahyouni, R., et al.: Google translate in healthcare: preliminary evaluation of transcription, translation and speech synthesis accuracy. BMJ Innovations 7(2), 201–347 (2021)

5. Ajitha, P., Sivasangari, A., Rajkumar, R.I., et al.: Design of text sentiment analysis tool using feature extraction based on fusing machine learning algorithms. J. Intell. Fuzzy Syst. 40(1), 1–9 (2020)

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