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An Experiment on Lexical Stress in Pakistani English Speech
Abbasi A.M., Shaikh I.H., Bakhsh I., Khosh N.K.
to train machine learning models, which will increase the accuracy of voice recognition for English
IT diagnostics of Parkinson's disease based on voice markers and decreased motor activity
Vishniakou, U. A., Yiwei, X.
using machine learning, based on markers of voice analysis and changes in patient movements on known
Neuropsychological testing and machine learning distinguish Alzheimer's disease from other causes for cognitive impairment
Gurevich P., Stuke H., Kastrup A., Stuke H., Hildebrandt H.
(pathologically increased TB ratio) was predicted with a machine learning algorithm. To this end, the algorithm
Обнаружение и детектирование объектов на видеоизображении на основе машинного обучения
Туча, Д. Ю.
обеспечения. Software for object detection and recognition on video images using algorithm SSD
Preemptive scheduling of two uniform parallel machines to minimize total tardiness
Lushchakova, I. N.
We consider the problem of preemptive scheduling n jobs on two uniform parallel machines. All jobs
Application of machine learning methods to the problem of medical data analysis
Divakov D.V., Krasilnikova E.N., Khokhlacheva Y.D., Khokhlov A.A.
of tools such as machine learning algorithms as applied to patient diagnosis (e.g., analysis of CT scans
Application Identification in mmWave/THz Systems via Machine Learning Algorithms
Dugaeva Svetlana, Begishev Vyacheslav, Stepanov Nikita
is in a stationary position. In this paper, by utilizing machine learning (ML) algorithms, we propose a
The modular structure of the adaptive machine learning system
Lomakin, V. V., Asadullaev, R. G., Mamatov, A. V., Pogorelyy, M. U., Mishunin, V. V.
Machine learning system based on the modular structure can tune to particular subject area flexibly
Machine learning methods for evaluating innovative projects
Shmeleva, A., Goldobin, I., Klimova, E., Moskvin, A., Lygarev, Y.
The use of mathematical methods and machine learning algorithms based on them for solving applied
Machine Learning Techniques in Diagnostics and Prediction of the Clinical Features of Schizophrenia: A Narrative Review
Gashkarimov, Vadim Rimovich, Sultanova, Renata Ildarovna, Efremov, Ilya Segeevich, Asadullin, Azat
of MRI, EEG, and actigraphy findings. Also, models created using machine learning algorithms can analyze

Страница 11 из 3782

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