Нүүр зураг

Artificial intelligence and multimodal signal processing in human-machine interaction /

"Presents an overview of an emerging field that is concerned with exploiting multiple modalities of communication in both artificial intelligence and human-machine interaction. The book not only provides cross disciplinary research in the fields of multimodal signal acquisition and sensing, ana...

Бүрэн тодорхойлолт

-д хадгалсан:
Номзүйн дэлгэрэнгүй
Бусад зохиолчид: Subasi, Abdulhamit (Засварлагч), Qaisar, Saeed Mian (Засварлагч), Nisar, Humaira, 1970- (Засварлагч)
Формат: Цахим Цахим ном
Хэл сонгох:англи
Хэвлэсэн: London, United Kingdom ; San Diego, CA : Academic Press, an imprint of Elsevier, [2025]
Цуврал:Artificial intelligence applications in healthcare and medicine (Series)
Нөхцлүүд:
Biosensors.
Signal processing > Digital techniques.
Artificial intelligence > Medical applications.
Human-computer interaction.
Brain-computer interfaces.
Artificial intelligence.
Intelligence artificielle.
Biocapteurs.
Traitement du signal > Techniques numériques.
Interfaces cerveau-ordinateur.
artificial intelligence.
Artificial intelligence
Artificial intelligence > Medical applications
Biosensors
Brain-computer interfaces
Human-computer interaction
Signal processing > Digital techniques
Онлайн хандалт:ScienceDirect
Шошгууд: Шошго нэмэх
Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!
Агуулга:
  • Chapter 1. Introduction to human-machine interaction
  • Chapter 2. Artificial intelligence techniques for human-machine interaction
  • Chapter 3. Feature extraction techniques for human-computer interaction
  • Chapter 4. An overview of techniques and best practices to create intuitive and user-friendly human-machine interfaces
  • Chapter 5. An overview of electroencephalogram based human-computer interface
  • Chapter 6. Speech-driven human-machine interaction using Mel-frequency Cepstral coefficients with machine learning and Cymatics Display
  • Chapter 7. EEG-based brain-computer interface using wavelet packet decomposition and ensemble classifiers
  • Chapter 8. Understanding dyslexia and the potential of artificial intelligence in detecting neurocognitive impairment in dyslexia
  • Chapter 9. Early dementia detection and severity classification with deep SqueezeNet convolutional neural network using EEG images
  • Chapter 10. EEG-based stress identification using oscillatory mode decomposition and artificial neural network
  • Chapter 11. EEG signal processing with deep learning for alcoholism detection
  • Chapter 12. ECG-based emotion recognition using CWT and deep learning
  • Chapter 13. EOG-based human-machine interaction using artificial intelligence
  • Chapter 14. Surface EMG-based gesture recognition using wavelet transform and ensemble learning
  • Chapter 15. EEG-based secure authentication mechanism using discrete wavelet transform and ensemble machine learning methods
  • Chapter 16. EEG-based emotion recognition using AR burg and ensemble machine learning models
  • Chapter 17. Immersive virtual reality and augmented reality in human-machine interaction
  • Chapter 18. Mental workload levels of multiple sclerosis patients in the virtual reality environment
  • Chapter 19. Vision-based action recognition for the human-machine interaction
  • Chapter 20. Security and privacy in human-machine interaction for healthcare.

Ижил төстэй зүйлс