Five-Layer Intelligence of the Machine Brain

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Details

This book intends to report the new results of the efforts on the study of Layered Intelligence of the Machine Brain (LIMB). The book collects novel research ideas in LIMB and summarizes the current machine intelligence level as five layer intelligence- environments sensing, active learning, cognitive computing, intelligent decision making and automatized execution. The book is likely to be of interest to university researchers, R&D engineers and graduate students in computer science and electronics who wish to learn the core principles, methods, algorithms, and applications of LIMB.


The first book introducing the machine brain as five-layer intelligence Presents a theoretical explanation on the real intelligence with face recognition examples. Includes a whole framework of technologies in system modelling and simulation.

Autorentext

Wenfeng Wang is currently a full professor of School of Electrical and Electronic Engineering, Shanghai Institute of Technology and the director of International Academy of Visual Art and Engineering LTD. He has been invited as the editor in chief of International Journal of Electronics and Electrical Engineering. He is also a key talent in Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences (2018- ). A reviewer of many SCI journals, including some top journals - Water Research, Science China-Information Sciences, Science of the Total Environment, Environmental Pollution, IEEE Transactions on Automation Science and Engineering and etc. A keynote speaker of AMICR2019, IACICE2020, OAES2020, AICS2021, 3DIT-MSP&DL2020 and etc. A scientist in chief of RealMax, Shanghai Lingang Artificial Intelligence Laboratory and etc.
Xi Chen is currently leader at Xinjiang Branch Chinese Academy of Sciences (CAS). He received Ph.D. from Wuhan University in 2003. He is an outstanding youth winner of CAS, an expert enjoying special government allowance, a national excellent worker. He received special prize of science and technology progress award of Xinjiang Autonomous Region, a gold award of Heliang Heli, an advanced individual of innovation and culture of CAS, a national candidate for the new century talent project, and outstanding expert of Urumqi, top 10 of Xinjiang Uygur Autonomous Region. He is also president of NEESPI-Central Asia, vice president of China Society of natural resources, executive director of China Association of remote sensing applications, President of Xinjiang Society of natural resources and President of Xinjiang Association of remote sensing applications. Tuozhong Yao is an associate Professor in Ningbo University of Technology, China. He once served as an intellectual property expert of Ningbo "invention patent incremental quality improvement service project" and a member of the intellectualproperty expert group of Ningbo intermediate people's court. His main research direction is computer vision and machine learning. He has published nearly 20 SCI/EI papers and undertaken a number of national and Provincial Natural Science Foundation projects.


Inhalt
Structure of a machine brain.- The first intelligence layer - environments sensing.- The second intelligence layer - active learning.- The third intelligence layer - cognitive computing.- The fourth intelligence layer - intelligent decisions making.- The fifth intelligence layer - automatized execution.- Applications in Face Recognition Access Control Manufacturing.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09789811902710
    • Lesemotiv Verstehen
    • Genre Electrical Engineering
    • Auflage 1st edition 2022
    • Sprache Englisch
    • Anzahl Seiten 228
    • Herausgeber Springer Nature Singapore
    • Größe H241mm x B160mm x T18mm
    • Jahr 2022
    • EAN 9789811902710
    • Format Fester Einband
    • ISBN 9811902712
    • Veröffentlichung 16.03.2022
    • Titel Five-Layer Intelligence of the Machine Brain
    • Autor Wen-Feng Wang , Tuozhong Yao , Xi Chen
    • Untertitel System Modelling and Simulation
    • Gewicht 512g

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