Parallel Approaches to Accelerate Deep Learning Processes Using Heterogeneous Computing
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-60997-8_4
Reference19 articles.
1. Abdusalomov, A.B., Nasimov, R., Nasimova, N., Muminov, B., Whangbo, T.K.: Evaluating synthetic medical images using artificial intelligence with the GAN algorithm. Sensors 23, 3440 (2023). https://doi.org/10.3390/s23073440
2. Rakhimov, M., Akhmadjonov, R., Javliev, S.: Artificial intelligence in medicine for chronic disease classification using machine learning. In: 2022 IEEE 16th International Conference on Application of Information and Communication Technologies (AICT), Washington DC, DC, USA, pp. 1–6 (2022). https://doi.org/10.1109/AICT55583.2022.10013587
3. Tagmatova, Z., Abdusalomov, A., Nasimov, R., Nasimova, N., Dogru, A.H., Cho, Y.-I.: New approach for generating synthetic medical data to predict type 2 diabetes. Bioengineering 10, 1031 (2023). https://doi.org/10.3390/bioengineering10091031
4. Abdusalomov, A.B., Safarov, F., Rakhimov, M., Turaev, B., Whangbo, T.K.: Improved feature parameter extraction from speech signals using machine learning algorithm. Sensors 22, 8122 (2022). https://doi.org/10.3390/s22218122
5. Rakhimov, M.: Algorithm for parallel processing of a speech signal based on the Haar wavelet. In: 2022 International Conference on Information Science and Communications Technologies (ICISCT), Tashkent, Uzbekistan, pp. 1–4 (2022). https://doi.org/10.1109/ICISCT55600.2022.10146906
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