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Recent Advances in Computational Intelligence Applications for Biometrics and Biomedical Devices focuses on the intersection of biometric-driven computational approaches and techniques within a connected multi-modal environment, particularly emphasizing their applications in healthcare. The book explores cutting-edge methodological approaches that leverage technologies like blockchain and integrate them with information fusion, data security for medical devices, and trust management. Readers with find this to be a comprehensive overview of the topics covered, including machine learning and deep learning for biomedical-based biometrics, computational medical imaging techniques, security strategies for healthcare systems, AI technology for multimodal biometrics, and feature reduction techniques.

Other sections cover blockchain and fog computing models for medical sensor data storage and evolutionary optimization for biometric feature identification and recognition, amongst others.

  • Covers recent computational advancements in biomedical-driven biometrics for connected healthcare
  • Explores intelligent computational multimodal technologies for healthcare, incorporating deep learning, parallel computing, and distributed computing
  • Presents security aspects of next-generation healthcare technologies, including machine learning, deep learning, and blockchain integration with IoT for information fusion, data security, and trust management
  • Provides both fundamental and high-level concepts, making it suitable for both industry professionals and beginners
  • Includes applications of cloud and pervasive computing technologies in biometrics for real-world scenarios

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