ICMLSC 2022

Welcome to The 6th ICMLSC 2022

International Conference on Machine Learning and Soft Computing

第六届机器学习与软计算国际会议欢迎您！| 中国海口， 1月15-17日

ICMLSC 2022, The 6th International Conference on Machine Learning and Soft Computing, will take place in Haikou, China, from January 15-17, 2022. ICMLSC conference is co-sponsored by Sai Gon University, Vietnam, Industrial University of Ho Chi Minh City and Hosei University, Japan, with support from Chuo University, Japan, International University - Vietnam National University, Vietnam, Can Tho University, Vietnam, etc.

The last 5 years, ICMLSC has been to Virtual (due to impact of COVID-19), Haiphong City, Da Lat, Phu Quoc Island and Ho Chi Minh City. This conference is highlighted by more and more audiences who joined us. We look forward to your participation and continued engagement at future ICMLSC series.

ICMLSC Call For Papers Flyer

人工智能一直是计算机科学的前沿和热点领域。21世纪后随着神经网络、遗传算法等新算法的成熟，以及“深度学习”领域核心问题的突破，人工智能的热潮再次来临。机器学习的应用已遍及人工智能的各个分支，如专家系统、自动推理、自然语言理解、模式识别、计算机视觉、智能机器人等领域。

2022年第六届机器学习与软计算国际会议将于1月15-17日在中国海口召开，会议旨在为相关领域的专家学者从业人员提供一个交流学习，寻求合作机会的平台。

会议征稿环节已正式启动！！欢迎在线投稿，请点击。

ICMLSC Tracks

Track 1: Data Science and Computing Chair: Prof. Naoyuki Ishimura, Chuo University, Japan Co-chair: Prof. Takahiko Fujita, Chuo University, Japan	Track 2: Artificial Intelligence and Digital Transformation Chair: A/Prof. (HDR) Hiep Xuan Huynh, Can Tho University, Vietnam Co-chair: A/Prof. Nhat Minh Viet Vo, Hue University, Vietnam

Track 3: Intelligent Computing and Application Chair: Prof. Pham The Bao, Sai Gon University, Vietnam	Track 4: Image Processing and Recognition Chair: Prof. Huynh Trung Hieu, Industrial University of Ho Chi Minh City, Vietnam

Proceedings

Full Paper submitted and accepted after successful registration will be published in the ACM Conference Proceedings (ISBN: 978-1-4503-8747-7), which will be archived in ACM Digital Library, and indexed by Ei Compendex, Scopus.
被录用并报告的文章将一如既往地由ACM会议论文集（刊号：978-1-4503-8747-7）出版，提交ACM数据库，Ei核心，Scopus等检索。

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Special Issue

Extend Papers after selection will be recommended to Machine Learning and Knowledge Extraction (ISSN: 2504-4990)
High Visibility: indexed within ESCI (Web of Science), dblp, and many other databases.