International Conference on Signal Processing and Machine Learning on July 15-17, 2025 in Hohhot, China

International Conference on Signal Processing and Machine Learning on July 15-17, 2025 in Hohhot, China

SPML 2025 information:

1. SPML 2025 is co-organized by Inner Mongolia University, China and China University of Mining and Technology, China.

2. Accepted papers will be published in the International Conference Proceedings, which will be indexed by EI Compendex, Scopus, and submitted to be reviewed by Thomson Reuters Conference Proceedings Citation Index (ISI Web of Science).

3. Prof. Haijun Zhang from University of Science and Technology Beijing, China (IEEE Fellow) and Prof. Haipeng Yao, Beijing University of Posts and Telecommunications, China (IET Fellow) will be the keynote speakers.

4. Publication:

All the accepted and registered papers in SPML 2020 have been published into ACM conference proceedings (ISBN: 978-1-4503-7573-3), which have been indexed by EI Compendex and Scopus.

All the accepted and registered papers in SPML 2021 have been published into ACM conference proceedings (ISBN: 978-1-4503-9017-0), which have been indexed by EI Compendex and Scopus.

All the accepted and registered papers in SPML 2022 have been published into ACM conference proceedings (ISBN: 978-1-4503-9691-2), which have been indexed by EI Compendex and Scopus.

All the accepted and registered papers in SPML 2023 have been published into ACM conference proceedings (ISBN: 979-8-4007-0757-5), which have been indexed by EI Compendex and Scopus.

 

Conference Venue:

Inner Mongolia University, China

Address: QM5P+H55, Yuquan District, Hohhot, Inner Mongolia, China, 010031

 

Submission and Contact Methods:

Submission Methods: https://www.zmeeting.org/submission/SPML2025

E-mail: [email protected]

Conference Specialist: Ms. Willow Wong

Wechat: 18149749902

Computer Vision & Virtual Reality

Image Processing & Understanding

Image/Video Processing and Coding

Natural Language Processing

Machine learning methods

Learning and adaptive control

Learning/adaption of recognition and perception

Learning for Handwriting Recognition

Learning in Image Pre-Processing and Segmentation

Learning in process automation

Learning of appropriate behaviour

Learning of action patterns

Learning robots

Feature extractions

Support vector machines (SVM)

Least-squares SVM (LS-SVM)

Name: ACMSC
Website: http://www.acm-sg.org/

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