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 2021 4th International Conference on Signal Processing and Machine Learning (SPML 2021)

2021 4th International Conference on Signal Processing and Machine Learning (SPML 2021)

SPML 2021

Date of beginning

Wednesday, 18 August 2021

Duration

3 days

Deadline for abstracts

Friday, 30 July 2021

City

Beijing

Country

China

Contact

Mr. Paul Choo

E-Mail

This email address is being protected from spambots. You need JavaScript enabled to view it.

Memo

SPML 2021 information: 1. SPML 2021 is supported by ACM Singapore Chapter.2. Accepted papers will be published in the Conference Proceedings by ACM, 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. Yongfeng Huang from Tsinghua University in China, Prof. Shigeru Katagiri from Doshisha University in Japan, Prof. Chin-Chen Chang from Feng Chia University in Taiwan and Prof. Yen-Wei Chen from Ritsumeikan University in Japan will be the keynote speakers4. SPML 2018 was held on 28-30 November 2018 in Shanghai, China and SPML 2019 on 27-29 November 2019 in Hangzhou, China, all the published proceedings have been indexed by EI Compendex, Scopus. Due to the COVID-19 pandemic, SPML 2020 was special arranged into online conference during Oct. 22-24 , 2020.Conference VenueBeijing, ChinaSubmission and Contact MethodsSubmission Methods: Easy Chair System: http://www.easychair.org/conferences/?conf=spml2021E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.nce Specialist: Mr. Paul ChooSPML 2021 can provide a better platform for academic communication in Signal Processing and Machine Learning in theoretical and practical aspects.For more conference information, please visit the conference website: http://www.spml.netCall for PapersAdaptive Filtering & Signal ProcessingAd-Hoc and Sensor NetworksAnalog and Mixed Signal ProcessingDSP Implementations and Embedded SystemsEmerging TechnologiesSignal Processing Theory and MethodsMachine learning methods........