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Augmented Coaching Ecosystem for Non-obtrusive Adaptive Personalized Elderly Care on the Basis of Cloud-Fog-Dew Computing Paradigm.

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Deep Learning for Fatigue Estimation on the Basis of Multimodal Human-Machine Interactions., , , , , and . CoRR, (2018)Hybrid Classic-Quantum Neural Networks for Image Classification., , , , , and . IDAACS, page 968-972. IEEE, (2021)Comparative Analysis of Open Source Frameworks for Machine Learning with Use Case in Single-Threaded and Multi-Threaded Modes., , , , , and . CoRR, (2017)Convolutional and Recurrent Neural Networks for Physical Action Forecasting by Brain-Computer Interface., , , , , and . IDAACS, page 973-978. IEEE, (2021)Augmented Coaching Ecosystem for Non-obtrusive Adaptive Personalized Elderly Care on the basis of Cloud-Fog-Dew computing paradigm., , , , , , , , , and 2 other author(s). MIPRO, page 359-364. IEEE, (2017)Edge Intelligence Resource Consumption by UAV-based IR Object Detection., , , , , , and . UAVM, page 57-61. ACM, (2023)Prediction of Physical Load Level by Machine Learning Analysis of Heart Activity after Exercises., , , , , and . SSCI, page 557-562. IEEE, (2019)Impact of Mixed Multimodalities and Size Dependence on Performance of Object Detection on Multimodal Satellite Imagery*., , , , , and . IEEE Big Data, page 2157-2162. IEEE, (2023)Context-Aware Data Augmentation for Efficient Object Detection by UAV Surveillance., , , and . ISDFS, page 1-6. IEEE, (2022)Comparative analysis of open source frameworks for machine learning with use case in single-threaded and multi-threaded modes., , , , and . CSIT (1), page 373-376. IEEE, (2017)