Conference Information
WSPML 2022: International Workshop on Signal Processing and Machine Learning
https://www.wspml.org/
Submission Date:
2022-11-15 Extended
Notification Date:
2022-11-20
Conference Date:
2022-12-16
Location:
Beijing, China
Years:
4
Viewed: 9540   Tracked: 10   Attend: 3

Call For Papers
2022年第四届信号处理与机器学习国际研讨会(WSPML 2022)

重要信息
会议网址:www.wspml.org
会议时间:2022年12月2-4日
召开地点:中国北京
截稿时间:2022年10月31日
录用通知:投稿后2周内
收录检索:EI,Scopus

会议简介
★2022年第四届信号处理与机器学习国际研讨会(WSPML 2022)---Ei Compendex&Scopus-Call for papers
|2022年12月2-4日,中国北京|网址: www.wspml.org

★WSPML 2022将围绕“信号处理与机器学习”的最新研究领域而展开,为研究人员,工程师和学者,以及行业专业人士提供一个平台并介绍他们的最新的研究成果以及今后开发的活动,为参会人员们交流新的思想和应用经验建立业务或研究关系。本次会议将于2021年12月1-3日在中国北京召开,在会议期间您将有机会聆听到前沿的学术报告,见证该领域的成果与进步。

会议日程预览:
会议时间	                内容
2022年12月2日	注册+接待
2022年12月3日	开幕式+KN演讲+分会场报告
2022年12月4日	分会场报告+实验室参观

关于出版和索引
所有接受的论文将在线出版,将被Ei Compendex,SCOPUS,Google Scholar,Cambridge Scientific Abstracts(CSA),Inspec, ISTP等检索,优秀论文将在国际期刊上发表。

特邀主讲人

Zaid Harchaoui教授——华盛顿大学,美国


征稿主题/会议征稿
自适应滤波与信号处理
adhoc网络与传感器网络
模拟和混合信号处理
应用(生物医学信号、生物计量学、生物信息学)
多通道自适应信号处理
阵列信号处理
人工神经网络
调制和信道编码
音频和电声学
自然语言处理
从序列中挖掘运动
音频/语音处理和编码

更多征稿主题请访问: http://www.wspml.org/cfp.htmls

参会方式
1.作者参会:一篇会议录用文章允许一名作者参会;
2.主讲嘉宾:申请主题演讲,由会务组审核;
3.口头演讲:申请口头报告,时间为15分钟;
4.海报参会:申请海报参会,根据官网模板准备海报,再录制5分钟视频;
5.视频参会:录制个人视频15分钟即可;
6.听众参会:不投稿仅参会,可参与问答,也可演讲及展示。

投稿方式
1.会议邮箱:wspml@hksra.org
2.CMT在线投稿:https://cmt3.research.microsoft.com/WSPML2022

请作者按照官网模板格式进行排版。排版好的论文全文(word+pdf版)发送至CMT在线系统或者会议邮箱。
提交摘要:即只参会做报告,不出版文章;
提交全文:即做参会做报告,并且出版文章;
听众:则不需要提交稿件,注册成功的听众可以参加会议的所有分会;

投稿要求:
1. 大会官方语言为英语,必须为全英文稿件,且应具有学术或实用价值,未在国内外学术期刊或会议发表过;
2. 保证文章原创性,未在国内外公开刊物或其它学术会议上发表过。
3. 文章篇幅一般在5-12页之间,不少于5页,含公式图表等,超过6页将收取超页费;
4. 作者可通过Turnitin或其他查询系统自费查重,重复率不得超过30%,由文章重复率引起的被拒稿将由作者自行承担责任;
5.文章录用:若您的文章被录用,我们将以邮件形式通知您,您将收到以下文件:录用通知、审稿意见表、中文注册表。

联系我们
会议秘书:谢女士
会议官网:www.wspml.org
会议邮箱:wspml@hksra.org
电话/微信同号:18108159229
QQ咨询:2011307354


WSPML solicits original, unpublished and novel papers for research publication and presentation in research track, and industry/application papers in application track. Articles in all areas of Signal Processing and Machine Learning are of interest, including the following:

Adaptive Filtering & Signal Processing 
Ad-Hoc and Sensor Networks
Analog and Mixed Signal Processing
Applications (biomedical signals, biometrix, bioinformatics)
Multichannel adaptive signal processing
Array Signal Processing
Artificial neural network (ANN)
Modulation and Channel Coding
Audio and Electroacoustics 
Natural Language Processing
Mining Motion from Sequence
Audio/Speech Processing and Coding
Bayesian and distributed learning
Bioimaging and Signal Processing 
Mining Images in Computer Vision
Biometrics & Authentification
Biosignal Processing & Understanding
Multimedia Signal Processing 
Classification and pattern recognition
Multimedia & Human-computer Interaction
Classification techniques
Cognitive information processing
Communication and Broadband Networks
Communication Signal processing
Multiset data analysis
Computational Intelligence
Computer Vision & Virtual Reality
Cryptography and Network Security
Data-driven adaptive systems
Data-driven models
Design and Implementation of Signal Processing Systems 
Multimedia Communications
Digital Signal Processing 
DSP Implementations and Embedded Systems 
Multimodal data fusion
Emerging Technologies 
Extreme learning machine (ELM)
Feature extractions
Genomic signals and  sequences
Graphical models and kernel methods
Hardware Implementation for Signal Processing
Higher Order Spectral Analysis
Image and Multidimensional Signal Processing 
Image Processing & Understanding
Image/Video Processing and Coding
Industry Technology 
Internet Signal Processing
Kernel design
Kernel methods and graphical models
Learning and adaptive control
Learning for Handwriting Recognition
Learning in Image Pre-Processing and Segmentation
Learning in process automation
Learning of action patterns
Learning of appropriate behavior
Learning robots
Learning theory
Learning/adaption of recognition and perception
Least-squares SVM (LS-SVM)
Machine Learning for Signal Processing
Machine learning methods
Mining Images and Texture
Network Analysis and Intrusion Detection
Neural Methods
Neural networks
Next Generation Mobile Communications
Nonlinear signal processing
Optical Communications
Parallel and Distributed Processing
PDE for Image Processing
Perceptual signal processing
Radar Signal Processing 
Rapid Prototyping and Tools for DSP Design 
RF and Wireless Communications
Sensor Array and Multi-channel Processing
Signal Processing and Communications Education
Signal Processing for Communications
Signal Processing for Security
Signal Processing Theory and Methods
Smart Grid, games, social networks
Sparsity-aware learning
Subspace/manifold learning
Support vector machines (SVM)
Twin SVM (TWSVM)
Last updated by Dou Sun in 2022-05-22
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