TY  - BOOK
ED  - Beyerer, Jürgen
ED  - Maier, Alexander
ED  - Niggemann, Oliver
AB  - This open access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains selected papers from the fifth international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Berlin, March 12-13, 2020. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.
DO  - 10.1007/978-3-662-62746-4
ID  - OAPEN ID: ONIX_20210113_9783662627464_8
ID  - OAPEN ID: https://library.oapen.org/handle/20.500.12657/46102
ID  - OAPEN ID: 51300
KW  - Cyber-physical systems, IoT
KW  - Communications Engineering, Networks
KW  - Computer Systems Organization and Communication Networks
KW  - Cyber-Physical Systems
KW  - Computer Engineering and Networks
KW  - Machine Learning
KW  - Artificial Intelligence
KW  - Cognitive Robotics
KW  - Internet of Things
KW  - Computational intelligence
KW  - Computer-based algorithms
KW  - Smart grid
KW  - Open Access
KW  - Industry 4.0
KW  - Electrical engineering
KW  - Cybernetics & systems theory
KW  - Communications engineering / telecommunications
KW  - Computer networking & communications
L1  - https://library.oapen.org/bitstream/20.500.12657/46102/1/2021_Book_MachineLearningForCyberPhysica.pdf
LA  - English
LK  - https://directory.doabooks.org/handle/20.500.12854/33766
PB  - Springer Nature
PY  - 2021
TI  - Machine Learning for Cyber Physical Systems : Selected papers from the International Conference ML4CPS 2020
ER  - 
