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EI, Scopus-icaipr 2021 : 2021 International Conference on Artificial Intelligence and Pattern Recognition


Link: http://WWW.ICAIPR.ORG
When Jun 25, 2021 - Jun 27, 2021
Where Beijing, China
Submission Deadline Jun 10, 2021
Notification Due Jun 15, 2021
Final Version Due Jun 20, 2021
Categories    artificial intelligence   pattern recognition   computer vision and robot visi   biomedical image analysis and

Call For Papers

( EI , Scopus ) 2021 International Conference on Artificial Intelligence and Pattern Recognition – (ICAIPR 2021) will be held in Beijing, China during June 25-27, 2021.

ICAIPR is an annual conference which aims to present the latest research and results of scholars and experts related to Artificial Intelligence and Pattern Recognition. This conference provides opportunities for delegates from different areas to exchange new ideas, applications and experiences face to face, to establish business or research relations, and to find global partners for future collaboration. We hope that the conference results in significant contributions to the knowledge base in these scientific fields.

ICAIPR 2021 will be held during June 25-27, 2021 in Beijing, China. It features keynote speech, invited speech as well as paper presentation with oral or poster. It is welcomed that scholars and experts from all over the world to submit the papers or register as listener to participate in the conference.

Please visit conference official website for more information:

[ Publication ]

Submitted conference papers will be blind peer reviewed by competent reviewers. The accepted and registered papers will be published in Conference Pcoceedings, which is indexed by Scopus, Conference Proceedings Citation Index—Science (CPCI-S) (Thomson Reuters, Web of Science), Chemical Abstracts etc.

[ Call for Paper ]

Include but not limited:
• Statistical, syntactic and structural pattern recognition
• Machine learning and data mining
• Artificial neural networks
• Dimensionality reduction and manifold learning
• Classification and clustering
• Graphical Models for Pattern Recognition
• Representation and analysis in pixel/voxel images
• Support vector machines and kernel methods
• Symbolic learning
• Active and ensemble learning
• Deep learning
• Pattern recognition for big data
• Transfer learning
• Semi-supervised learning and spectral methods
• Model selection
• Reinforcement learning and temporal models
• Performance Evaluation
• Depth & range sensor data processing and analysis
• Human computer interaction
• Coding, compression and super-resolution

For more topics, please check via

[ Submission ]

Make a submission via Easychair:

[ Contact us ]
Ms. Alice Zhang

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