Conference Description:

2022 2nd International Conference on Machine Learning and Intelligent Systems Engineering (MLISE 2022)

Website URL: http://mlise.org
Conference Date:August 5-7, 2022.
Location: Guangzhou, China
Official Email: [email protected]

[About the conference]
The 2022 2nd International Conference on Machine Learning and Intelligent Systems Engineering (MLISE 2022) will be held in Guangzhou, China during August 5-7, 2022.
MLISE is an annual conference which explores the development and implications in the related fields of Machine Learning and Intelligent Systems Engineering with an objective to present the novel and fundamental advancements. It also serves to foster communication among researchers and practitioners working in a wide variety of scientific areas with a common interest in improving Machine Learning and Intelligent Systems Engineering. Featured with invited speeches and paper presentations, MLISE 2022 welcomes submission of researches concerning any branch of Machine Learning and Intelligent Systems Engineering. Sincerely invite you to attend the conference.

[Co-Organizer]
Southwest University of Science and Technology
GSRA Conference

[Keynote Speakers]
Prof. Jianjun Ni, Hohai University, China(IEEE Senior Member)
Prof. Xiaofang Yuan , Hunan University, China
Prof. KANNIMUTHU SUBRAMANIYAM, Karpagam College of Engineering, India
Assoc. Prof. Yin Long, Southwest University of Science and Technology, China


[Publication]
All papers, both invited and contributed, will be reviewed by two or three experts from the committees. After a careful reviewing process, all accepted papers of MLISE 2022 will be published by IEEE Conference Publishing Services (CPS) and will be submitted to IEEE Xplore, EI Compendex, Scopus for indexing.

[Call For Papers]
Other related topics (http://mlise.org/a/Call_For_Papers/)

Machine Learning
Deep and Reinforcement learning
Pattern recognition and classification for networks
Machine learning for network slicing optimization
Machine learning for 5G system
Machine learning for user behavior prediction
New innovative machine learning methods
Optimization of machine learning methods
Performance analysis of machine learning algorithms
Experimental evaluations of machine learning
Data mining in heterogeneous networks
Machine learning for multimedia

Intelligent Systems Engineering
Intelligent control theory
Intelligent control system
Intelligent information systems
Intelligent data mining
AI and evolutionary algorithms
Distributed AI algorithms and technique
Distributed AI systems and architectures
Neural networks and applications
Multi-mode dynamic perception and natural interactions
Robot navigation, positioning and autonomous control
Robot perception and data fusion

[Contact Us]
Ms. Guo
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