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Machine Learning and Computational Intelligence Techniques for Data Engineering

Om Machine Learning and Computational Intelligence Techniques for Data Engineering

This book comprises the proceedings of the 4th International Conference on Machine Intelligence and Signal Processing (MISP2022). The contents of this book focus on research advancements in machine intelligence, signal processing, and applications. The book covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. It also includes the progress in signal processing to process the normal and abnormal categories of real-world signals such as signals generated from IoT devices, smart systems, speech, videos and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG), electromyogram (EMG), etc. This book proves to be a valuable resource for those in academia and industry.

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  • Språk:
  • Engelsk
  • ISBN:
  • 9789819900466
  • Bindende:
  • Hardback
  • Sider:
  • 912
  • Utgitt:
  • 16. mai 2023
  • Utgave:
  • 23001
  • Dimensjoner:
  • 160x51x241 mm.
  • Vekt:
  • 1679 g.
  • BLACK NOVEMBER
  Gratis frakt
Leveringstid: Ukjent

Beskrivelse av Machine Learning and Computational Intelligence Techniques for Data Engineering

This book comprises the proceedings of the 4th International Conference on Machine Intelligence and Signal Processing (MISP2022). The contents of this book focus on research advancements in machine intelligence, signal processing, and applications. The book covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. It also includes the progress in signal processing to process the normal and abnormal categories of real-world signals such as signals generated from IoT devices, smart systems, speech, videos and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG), electromyogram (EMG), etc. This book proves to be a valuable resource for those in academia and industry.

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