Human Brain and Artificial Intelligence
Second International Workshop, HBAI 2020, Held in Conjunction with IJCAI-PRICAI 2020, Yokohama, Japan, January 7, 2021, Revised Selected Papers
(Sprache: Englisch)
This book constitutes the refereed proceedings of the Second International Workshop on Human Brain and Artificial Intelligence, HBAI 2020, held in conjunction with IJCAI-PRICAI 2020, Kyoto, Japan, in January 2021. Due to the COVID-19 pandemic HBAI 2020 was...
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Klappentext zu „Human Brain and Artificial Intelligence “
This book constitutes the refereed proceedings of the Second International Workshop on Human Brain and Artificial Intelligence, HBAI 2020, held in conjunction with IJCAI-PRICAI 2020, Kyoto, Japan, in January 2021. Due to the COVID-19 pandemic HBAI 2020 was held in the year 2021 and transferred into virtual format. The 11 full papers presented were carefully reviewed and selected from 12 submissions. The papers present most recent research in the fields of brain-inspired computing, brain-machine interfaces, computational neuroscience, brain-related health, neuroimaging, cognition and behavior, learning, and memory, neuron modulation, and closed-loop brain stimulation.
Inhaltsverzeichnis zu „Human Brain and Artificial Intelligence “
ARLIF: A exible and efficient recurrent neuronal model for sequential tasks.- Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL.- Machines Develop Consciousness through Autonomous Programming for General Purposes (APFGP).- Incorporating Task-related Information in Dimensionality Reduction of Neural Population using Autoencoders.- Effective and Efficient ROI-wise Visual Encoding using an End-to-end CNN Regression Model and Selective Optimization.- Deep Insights into Graph Adversarial Learning: An Empirical Study Perspective.- Brain-Controlled Robotic Arm Based on Adaptive FBCCA.- Automatic Sleep Spindle Detection and Analysis in Patients with Sleep Disorders.- Diagnosing Parkinsons Disease Using Multimodal Physiological Signals.- Emotion recognition using multi-core tensor learning and multimodal physiological signal.- A review of transfer learning for EEG-based drivingfatigue detection.
Bibliographische Angaben
- 2021, 1st ed. 2021, VIII, 163 Seiten, 47 farbige Abbildungen, Maße: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Herausgegeben: Yueming Wang
- Verlag: Springer, Berlin
- ISBN-10: 9811612870
- ISBN-13: 9789811612879
Sprache:
Englisch
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