diff --git a/404.html b/404.html index 711f865..54e19e7 100644 --- a/404.html +++ b/404.html @@ -1 +1 @@ - Not Found

Not Found

← Back Home
+ Not Found

Not Found

← Back Home
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\nBruno Torresmi, Fance
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\nZeng Yong, UESTC, China
\nXiong Caidong, UESTC, China
\nXu Hongbing, UESTC, China

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Clarence De Silve, UBC, Canada
\nMo Jamishi, UT Dallas, USA
\nBruno Torresmi, Fance
\nTang Yuanyan, University of Macau, Macau, China
\nZeng Yong, UESTC, China
\nXiong Caidong, UESTC, China
\nXu Hongbing, UESTC, China

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ICCWAMTIP 2024, The 21th International Computer Conference on Wavelet Active Media Technology and Information Processing, will take place in Chengdu, China, from December 14th, 2024. This event is organized by University of Electronic Science and Technology of China(UESTC), sponsored by The National Natural Science Foundation of China(NSFC), National High Technology Research and Development Program of China and China International Talent Exchange Foundation. ICCWAMTIP 2024 is a not-to-be-missed opportunity that distills the most current knowledge on a rapidly advancing discipline in one conference. Join key researchers and established professionals in the field of information technologies as they assess the current state-of-the-art and roadmap crucial areas for future research.

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ICCWAMTIP 2024, The 21th International Computer Conference on Wavelet Active Media Technology and Information Processing, will take place in Chengdu, China, from December 14th, 2024. This event is organized by University of Electronic Science and Technology of China(UESTC), sponsored by The National Natural Science Foundation of China(NSFC), National High Technology Research and Development Program of China and China International Talent Exchange Foundation. ICCWAMTIP 2024 is a not-to-be-missed opportunity that distills the most current knowledge on a rapidly advancing discipline in one conference. Join key researchers and established professionals in the field of information technologies as they assess the current state-of-the-art and roadmap crucial areas for future research.

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"},40:function(a,e){a.exports="data:image/jpeg;base64,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"},41:function(a,e,t){a.exports=t.p+"images/static/images/tangyuanyan.33678029.jpg"},42:function(a,e,t){a.exports=t.p+"images/static/images/lijianping.ac82bdee.jpg"},49:function(a,e,t){"use 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"),n("div",{staticClass:"media-content"},[n("p",{staticClass:"title is-4"},[a._v("Zhang Jingzhong, Professor")]),a._v(" "),n("p",{staticClass:"subtitle is-6"},[a._v("Academician of Chinese Academy of Sciences, Chengdu Computer Applications Institute, Chinese Academy of Sciences")])])]),a._v(" "),n("div",{staticClass:"content"},[a._v("\n\t\t\tZhang Jingzhong, Professor, Academician of Chinese Academy of Sciences, Computer Scientist, Mathematician, Mathematics Educator. Academician Zhang was Professor of University of Science and Technology of China at some time in the past, and now he is the head of automated reasoning union laboratory of University of Electronic Science and Technology of China and Chengdu Computer Applications Institute, Chinese Academy of Sciences, the honorary director of education software institute of Guangzhou University, the chairman of National Digit Learning Centre of Huazhong Normal University. 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He invented the LianXiang method for augmenting the input of Chinese. From 1984 to 1995 he acted as the CTO of ICTC, i.e. The Company of ICT which was renamed as Legend in 1989 and Lenovo recently. He led the development of Legend Chinese System and Legend Series PC, which were the key products of the company and won the first-class prize of the State Award for Scientific and Technological Achievement in 1988 and 1992 respectively. For years he devoted himself to the development of the homegrown core technology as well as the IT industry of China. In 1994 he was elected as the Academician of Chinese Academy of Engineering. He was rewarded the Lifetime Achievement Award by the Chinese Information Processing Society of China (CIPS) and China Computer Federation (CCF) in 2011 and 2015 respectively.\n\t\t")])])]),a._v(" "),n("div",{staticClass:"card"},[n("div",{staticClass:"card-content"},[n("div",{staticClass:"media"},[n("div",{staticClass:"media-left"},[n("figure",{staticClass:"image"},[n("img",{staticStyle:{width:"250px"},attrs:{src:t(41),alt:"tangyuanyan"}})])]),a._v(" "),n("div",{staticClass:"media-content"},[n("p",{staticClass:"title is-4"},[a._v("Tang Yuanyan, Ph.D., Professor")]),a._v(" "),n("p",{staticClass:"subtitle is-6"},[a._v("Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macau, China")])])]),a._v(" "),n("div",{staticClass:"content"},[a._v("\n\t\t\tTang Yuanyan is a Chair Professor in Faculty of Science and Technology at University of Macau and Professor/Adjunct Professor/Honorary Professor at several institutes in China, USA, Canada, France, and Hong Kong. His current interests include wavelets, pattern recognition, image processing, and artificial intelligence. He has published more than 400 academic papers and is the author/coauthor of over 25 monographs/books/bookchapters. He is the Founder and Editor-in-Chief of International Journal on Wavelets, Multiresolution, and Information Processing (IJWMIP), and Associate Editors of several international journals. He is the Founder and Chair of pattern recognition committee in IEEE SMC. He has serviced as general chair, program chair, and committee member for many international conferences. Dr. Tang is the Founder and General Chair of the series International Conferences on Wavelets Analysis and Pattern Recognition (ICWAPRs). He is the Founder and Chair of the Macau Branch of International Associate of Pattern Recognition (IAPR). Dr. Y. Y. Tang is a Fellow of IEEE, and Fellow of IAPR.\n\t\t")])])]),a._v(" "),n("div",{staticClass:"card"},[n("div",{staticClass:"card-content"},[n("div",{staticClass:"media"},[n("div",{staticClass:"media-left"},[n("figure",{staticClass:"image"},[n("img",{staticStyle:{width:"250px"},attrs:{src:t(42),alt:"lijianping"}})])]),a._v(" "),n("div",{staticClass:"media-content"},[n("p",{staticClass:"title is-4"},[a._v("Li Jianping, Ph.D., Professor")]),a._v(" "),n("p",{staticClass:"subtitle is-6"},[a._v("International Centre for Wavelet Analysis and Its applications,Big Data Research Institute, School of Computer Science,University of Electronic Science and Technology of China（UESTC）")])])]),a._v(" "),n("div",{staticClass:"content"},[a._v("\n\t\t\tProfessor Dr. Li Jianping, male, born on October 11,1964. He received the B.S. degree in applied mathematics from Chongqing University, Chongqing, China, in 1986, the M. Eng. degree in software engineering and M. Sci. degree in computational mathematics from the Graduate School of Xi'an Jiaotong University, Xi'an, Shanxi, China, in 1989, and the Ph.D. degree in computer science from the Graduate School of Chongqing University, Chongqing, China, in 1998. From 1999 to 2000, he was a post doctoral and visiting professor working at Hong Kong Baptist University under the leadership of Professor Dr. Yuan Yan Tang. From 2002 to 2003, 2005 to 2006, and in 2010, 2011, 2013, 2014, 2015,he was a senior visiting professor working respectively at Provence University, France, University of Guelph, Canada, Washington University, USA, University of Zurich, Switzerland. He is presently a Professor in International Centre for Wavelets Analysis and Its Applications (ICWAA) of University of Electronic Science and Technology of China（UESTC）, Chengdu, China, and as a head of ICWAA, he is the dean of Big Data Research Institute of UESTC. Dr. Li has served as a Syndic for Awards of National Science and Technology of China, a founder of the International Journal on Multiresolution, Wavelets, Applications (IJMWA), a founder and Editor in Chief of International Progress on Wavelet Active Media Technology and Information Processing, and also as General Chairman of many international conferences, a reviewer for many international famous Journals. His book Wavelet Analysis & Signal Processing: Theory, Applications & Software Implementations, was awarded the second prize of National Science and Technology of China (1999), and it is very important reference for many scientists. Dr. Li has published more than 300 technical papers and is the author/ co-author of 30 books on subjects ranging from wavelet analysis and its applications to computer science. His current interests include wavelet theory and applications, fractal, image processing, pattern recognition, information security, big data, artificial intelligence.\n\t\t")])])])])},[],!1,null,null,null);"function"==typeof i&&i(r);e.default=r.exports}}]); \ No newline at end of file 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"},41:function(a,e){a.exports="data:image/jpeg;base64,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"},42:function(a,e,t){a.exports=t.p+"images/static/images/tangyuanyan.33678029.jpg"},43:function(a,e,t){a.exports=t.p+"images/static/images/lijianping.ac82bdee.jpg"},50:function(a,e,t){"use 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"),n("div",{staticClass:"media-content"},[n("p",{staticClass:"title is-4"},[a._v("Zhang Jingzhong, Professor")]),a._v(" "),n("p",{staticClass:"subtitle is-6"},[a._v("Academician of Chinese Academy of Sciences, Chengdu Computer Applications Institute, Chinese Academy of Sciences")])])]),a._v(" "),n("div",{staticClass:"content"},[a._v("\n\t\t\tZhang Jingzhong, Professor, Academician of Chinese Academy of Sciences, Computer Scientist, Mathematician, Mathematics Educator. Academician Zhang was Professor of University of Science and Technology of China at some time in the past, and now he is the head of automated reasoning union laboratory of University of Electronic Science and Technology of China and Chengdu Computer Applications Institute, Chinese Academy of Sciences, the honorary director of education software institute of Guangzhou University, the chairman of National Digit Learning Centre of Huazhong Normal University. 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He invented the LianXiang method for augmenting the input of Chinese. From 1984 to 1995 he acted as the CTO of ICTC, i.e. The Company of ICT which was renamed as Legend in 1989 and Lenovo recently. He led the development of Legend Chinese System and Legend Series PC, which were the key products of the company and won the first-class prize of the State Award for Scientific and Technological Achievement in 1988 and 1992 respectively. For years he devoted himself to the development of the homegrown core technology as well as the IT industry of China. In 1994 he was elected as the Academician of Chinese Academy of Engineering. He was rewarded the Lifetime Achievement Award by the Chinese Information Processing Society of China (CIPS) and China Computer Federation (CCF) in 2011 and 2015 respectively.\n\t\t")])])]),a._v(" "),n("div",{staticClass:"card"},[n("div",{staticClass:"card-content"},[n("div",{staticClass:"media"},[n("div",{staticClass:"media-left"},[n("figure",{staticClass:"image"},[n("img",{staticStyle:{width:"250px"},attrs:{src:t(42),alt:"tangyuanyan"}})])]),a._v(" "),n("div",{staticClass:"media-content"},[n("p",{staticClass:"title is-4"},[a._v("Tang Yuanyan, Ph.D., Professor")]),a._v(" "),n("p",{staticClass:"subtitle is-6"},[a._v("Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macau, China")])])]),a._v(" "),n("div",{staticClass:"content"},[a._v("\n\t\t\tTang Yuanyan is a Chair Professor in Faculty of Science and Technology at University of Macau and Professor/Adjunct Professor/Honorary Professor at several institutes in China, USA, Canada, France, and Hong Kong. His current interests include wavelets, pattern recognition, image processing, and artificial intelligence. He has published more than 400 academic papers and is the author/coauthor of over 25 monographs/books/bookchapters. He is the Founder and Editor-in-Chief of International Journal on Wavelets, Multiresolution, and Information Processing (IJWMIP), and Associate Editors of several international journals. He is the Founder and Chair of pattern recognition committee in IEEE SMC. He has serviced as general chair, program chair, and committee member for many international conferences. Dr. Tang is the Founder and General Chair of the series International Conferences on Wavelets Analysis and Pattern Recognition (ICWAPRs). He is the Founder and Chair of the Macau Branch of International Associate of Pattern Recognition (IAPR). Dr. Y. Y. Tang is a Fellow of IEEE, and Fellow of IAPR.\n\t\t")])])]),a._v(" "),n("div",{staticClass:"card"},[n("div",{staticClass:"card-content"},[n("div",{staticClass:"media"},[n("div",{staticClass:"media-left"},[n("figure",{staticClass:"image"},[n("img",{staticStyle:{width:"250px"},attrs:{src:t(43),alt:"lijianping"}})])]),a._v(" "),n("div",{staticClass:"media-content"},[n("p",{staticClass:"title is-4"},[a._v("Li Jianping, Ph.D., Professor")]),a._v(" "),n("p",{staticClass:"subtitle is-6"},[a._v("International Centre for Wavelet Analysis and Its applications,Big Data Research Institute, School of Computer Science,University of Electronic Science and Technology of China（UESTC）")])])]),a._v(" "),n("div",{staticClass:"content"},[a._v("\n\t\t\tProfessor Dr. Li Jianping, male, born on October 11,1964. He received the B.S. degree in applied mathematics from Chongqing University, Chongqing, China, in 1986, the M. Eng. degree in software engineering and M. Sci. degree in computational mathematics from the Graduate School of Xi'an Jiaotong University, Xi'an, Shanxi, China, in 1989, and the Ph.D. degree in computer science from the Graduate School of Chongqing University, Chongqing, China, in 1998. From 1999 to 2000, he was a post doctoral and visiting professor working at Hong Kong Baptist University under the leadership of Professor Dr. Yuan Yan Tang. From 2002 to 2003, 2005 to 2006, and in 2010, 2011, 2013, 2014, 2015,he was a senior visiting professor working respectively at Provence University, France, University of Guelph, Canada, Washington University, USA, University of Zurich, Switzerland. He is presently a Professor in International Centre for Wavelets Analysis and Its Applications (ICWAA) of University of Electronic Science and Technology of China（UESTC）, Chengdu, China, and as a head of ICWAA, he is the dean of Big Data Research Institute of UESTC. Dr. Li has served as a Syndic for Awards of National Science and Technology of China, a founder of the International Journal on Multiresolution, Wavelets, Applications (IJMWA), a founder and Editor in Chief of International Progress on Wavelet Active Media Technology and Information Processing, and also as General Chairman of many international conferences, a reviewer for many international famous Journals. His book Wavelet Analysis & Signal Processing: Theory, Applications & Software Implementations, was awarded the second prize of National Science and Technology of China (1999), and it is very important reference for many scientists. Dr. Li has published more than 300 technical papers and is the author/ co-author of 30 books on subjects ranging from wavelet analysis and its applications to computer science. His current interests include wavelet theory and applications, fractal, image processing, pattern recognition, information security, big data, artificial intelligence.\n\t\t")])])])])},[],!1,null,null,null);"function"==typeof i&&i(r);e.default=r.exports}}]); \ No newline at end of file diff --git a/_saber/js/page--timeline-md.fa28d13b.js b/_saber/js/page--timeline-md.37af7f1d.js similarity index 96% rename from _saber/js/page--timeline-md.fa28d13b.js rename to _saber/js/page--timeline-md.37af7f1d.js index 0cde6e0..1edae59 100644 --- a/_saber/js/page--timeline-md.fa28d13b.js +++ b/_saber/js/page--timeline-md.37af7f1d.js @@ -1 +1 @@ -(window.webpackJsonp=window.webpackJsonp||[]).push([[9],{50:function(t,e,n){"use strict";n.r(e);var o=n(0),r=function(t){var e,n,o=(n=void 0,{attributes:{slug:"timeline",title:"Conference Timeline",layout:e="page",createdAt:new Date(1718781944e3),updatedAt:new Date(1718781944e3),type:e,permalink:"/timeline.html"},internal:n,contentType:"markdown",content:n}),r=t.options.beforeCreate||[];t.options.beforeCreate=[function(){this.$page=o}].concat(r);["layout","transition"].forEach(function(e){var n=t.options.PageComponent;n&&(t.options[e]=n[e]),void 0===t.options[e]&&(t.options[e]=o.attributes[e])}),t.options.name="page-wrapper-"+o.attributes.slug.replace(/[^0-9a-z\-]/i,"-")},i=Object(o.a)({},function(){var t=this,e=t.$createElement,n=t._self._c||e;return n("layout-manager",[n("h2",{attrs:{id:"conference-timeline"}},[t._v("Conference Timeline")]),t._v(" "),n("table",[n("thead",[n("tr",[n("th",[t._v("Event")]),t._v(" "),n("th",[t._v("Schedule (China Standard Time, UTC+08:00)")])])]),t._v(" "),n("tbody",[n("tr",[n("td",[t._v("Submission")]),t._v(" "),n("td",[t._v("Deadline : "),n("strong",[t._v("Nov. 22th")])])]),t._v(" "),n("tr",[n("td",[t._v("Paper Review")]),t._v(" "),n("td",[t._v("From "),n("strong",[t._v("Oct. 30th")]),t._v(" to "),n("strong",[t._v("Nov. 30th")])])]),t._v(" "),n("tr",[n("td",[t._v("Author Notification")]),t._v(" "),n("td",[t._v("From "),n("strong",[t._v("Nov. 20th")]),t._v(" to "),n("strong",[t._v("Nov. 30th")])])]),t._v(" "),n("tr",[n("td",[t._v("Camera Ready Submission & Payment")]),t._v(" "),n("td",[t._v("Deadline : "),n("strong",[t._v("Dec. 3th")])])]),t._v(" "),n("tr",[n("td",[t._v("Conference")]),t._v(" "),n("td",[t._v("From "),n("strong",[t._v("Dec. 14th")]),t._v(" to "),n("strong",[t._v("Dec. 16th")])])])])])])},[],!1,null,null,null);"function"==typeof r&&r(i);e.default=i.exports}}]); \ No newline at end of file +(window.webpackJsonp=window.webpackJsonp||[]).push([[9],{51:function(t,e,n){"use strict";n.r(e);var o=n(0),r=function(t){var e,n,o=(n=void 0,{attributes:{slug:"timeline",title:"Conference Timeline",layout:e="page",createdAt:new Date(1718781944e3),updatedAt:new Date(1718781944e3),type:e,permalink:"/timeline.html"},internal:n,contentType:"markdown",content:n}),r=t.options.beforeCreate||[];t.options.beforeCreate=[function(){this.$page=o}].concat(r);["layout","transition"].forEach(function(e){var n=t.options.PageComponent;n&&(t.options[e]=n[e]),void 0===t.options[e]&&(t.options[e]=o.attributes[e])}),t.options.name="page-wrapper-"+o.attributes.slug.replace(/[^0-9a-z\-]/i,"-")},i=Object(o.a)({},function(){var t=this,e=t.$createElement,n=t._self._c||e;return n("layout-manager",[n("h2",{attrs:{id:"conference-timeline"}},[t._v("Conference Timeline")]),t._v(" "),n("table",[n("thead",[n("tr",[n("th",[t._v("Event")]),t._v(" "),n("th",[t._v("Schedule (China Standard Time, UTC+08:00)")])])]),t._v(" "),n("tbody",[n("tr",[n("td",[t._v("Submission")]),t._v(" "),n("td",[t._v("Deadline : "),n("strong",[t._v("Nov. 22th")])])]),t._v(" "),n("tr",[n("td",[t._v("Paper Review")]),t._v(" "),n("td",[t._v("From "),n("strong",[t._v("Oct. 30th")]),t._v(" to "),n("strong",[t._v("Nov. 30th")])])]),t._v(" "),n("tr",[n("td",[t._v("Author Notification")]),t._v(" "),n("td",[t._v("From "),n("strong",[t._v("Nov. 20th")]),t._v(" to "),n("strong",[t._v("Nov. 30th")])])]),t._v(" "),n("tr",[n("td",[t._v("Camera Ready Submission & Payment")]),t._v(" "),n("td",[t._v("Deadline : "),n("strong",[t._v("Dec. 3th")])])]),t._v(" "),n("tr",[n("td",[t._v("Conference")]),t._v(" "),n("td",[t._v("From "),n("strong",[t._v("Dec. 14th")]),t._v(" to "),n("strong",[t._v("Dec. 16th")])])])])])])},[],!1,null,null,null);"function"==typeof r&&r(i);e.default=i.exports}}]); \ No newline at end of file diff --git a/_saber/js/page--topics-md.6b9eb377.js b/_saber/js/page--topics-md.7914e34a.js similarity index 98% rename from _saber/js/page--topics-md.6b9eb377.js rename to _saber/js/page--topics-md.7914e34a.js index 89b82ec..03da0a0 100644 --- a/_saber/js/page--topics-md.6b9eb377.js +++ b/_saber/js/page--topics-md.7914e34a.js @@ -1 +1 @@ -(window.webpackJsonp=window.webpackJsonp||[]).push([[10],{51:function(n,i,e){"use strict";e.r(i);var t=e(0),o=function(n){var i,e,t=(e=void 0,{attributes:{slug:"topics",title:"Topics",layout:i="page",excerpt:"

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Gao Yuan, UESTC, China

Accepted abstract & Full paper will be invited to give the presentation at ICCWAMTIP 2024

+ Email: icacia@uestc.edu.cn

Our Links

diff --git a/contact.html b/contact.html index 656c2aa..872335e 100644 --- a/contact.html +++ b/contact.html @@ -5,7 +5,7 @@ footer[data-v-e541b38c]{background-color:#19181d;color:#b2b1b8}.title[data-v-e54 ICCWAMTIP Conference Flyer!

Everything you need to know here. -

Call for paper

Paper format

2024 21th ICCWAMTIP Secretariat

For more information about ICCWAMTIP, feel free to contact.

  • Tel. +86 (0)28-8683-1549

  • E-mail: icacia@uestc.edu.cn

  • WeChat QRCode (We will add you into our conference group):

Accepted abstract & Full paper will be invited to give the presentation at ICCWAMTIP 2024

diff --git a/guidance.html b/guidance.html index d6b92cd..f18de15 100644 --- a/guidance.html +++ b/guidance.html @@ -8,4 +8,4 @@ footer[data-v-e541b38c]{background-color:#19181d;color:#b2b1b8}.title[data-v-e54

Call for paper

Paper format

How to know the paper format of the conference?

Please pay an attention to the left side of this website, you can find PAPER FORMAT.

How to submit my paper?

We use CMT system to manager our conference this time.

  1. First you need to register an account in cmt system.
  2. Log in your account, then go to the submission page.
  3. Submit your paper.

How to know whether my paper is accepted by our conference?

Once your paper is accepted, we will send an email to you. And you can check your paper status all the time in the system.

About the paper fee.

Number of pages Fee
Less than 4 pages (include 4 pages) 2700￥
More than 4 pages,for each additional page 400￥

Example: 6 pages will be charged for 3500￥(2700+400×2).

More questions?

If you have any question about our conference, please send email to us or join our WeChat group in contact page.

Our email: icacia@uestc.edu.cn

Accepted abstract & Full paper will be invited to give the presentation at ICCWAMTIP 2024

+ Email: icacia@uestc.edu.cn

Our Links

diff --git a/images/QQGroup.jpg b/images/QQGroup.jpg new file mode 100644 index 0000000..bdd4ffb Binary files /dev/null and b/images/QQGroup.jpg differ diff --git a/index.html b/index.html index 79d6adc..a7748ca 100644 --- a/index.html +++ b/index.html @@ -24,4 +24,4 @@ footer[data-v-e541b38c]{background-color:#19181d;color:#b2b1b8}.title[data-v-e54 12:25 Question Time

12:30 Three Entrepreneur and Experts's Presentations

12:45 Closing Speech

Important Dates

Event Date (China Standard Time, UTC+08:00)
Submission Deadline November 22th, 2024
Notification Date November 30th, 2024
Conference Ceremony December 15th, 2024

CATALOG NUMBERS

Media Type Request Part Number ISBN Print ISSN Oline ISSN Media Qty Request
XPLORE COMPLIANT CFP21WAM-ART / / / 3
USB CFP21WAM-USB / / / 3
PRINT CFP21WAM-PRT / / / 2

Any question, please contact us by Conferene E-mail and Phone Number.

Accepted abstract & Full paper will be invited to give the presentation at ICCWAMTIP 2024

+ Email: icacia@uestc.edu.cn

Our Links

diff --git a/information.html b/information.html index 2a70ce9..83f95bd 100644 --- a/information.html +++ b/information.html @@ -11,4 +11,4 @@ The conference proceedings will be published by UESTC, all accepted papers are e Please log in the cmt system to submit your paper(strongly recommend), and you can also e-mail your paper directly to icacia@uestc.edu.cn.

Looking forward to seeing you in Chengdu!

And please notice the following date:

  • Submission closed: November 22th,2024
  • Acceptance notification: November 30th, 2024
  • Conference Ceremony: December 15th, 2024

CATALOG NUMBERS

Media Type Request Part Number ISBN Print ISSN Oline ISSN Media Qty Request
XPLORE COMPLIANT CFP21WAM-ART / / / 3
USB CFP21WAM-USB / / / 3
PRINT CFP21WAM-PRT / / / 2

Organization of the 21th ICCWAMTIP

International Centre for Wavelet Analysis and Its Applications

Chengdu China, UESTC

August 8th , 2024

Accepted abstract & Full paper will be invited to give the presentation at ICCWAMTIP 2024

+ Email: icacia@uestc.edu.cn

Our Links

diff --git a/news.html b/news.html index aedb7cf..0c1e99e 100644 --- a/news.html +++ b/news.html @@ -8,4 +8,4 @@ footer[data-v-e541b38c]{background-color:#19181d;color:#b2b1b8}.title[data-v-e54

Call for paper

Paper format

  • **
  • 2022-12-29: Add the final booklet of all papers, please download from this link
  • 2022-12-17: Updated the conference routine.
  • 2022-12-16: The conference will be held at 09:00 AM Dec. 19th, for the conference routine see bellow.
  • 2022-11-26: Advance the deadline for Camera Ready submission (including payment proof submission) from Dec. 8th to Dec. 3th
  • 2023-11-8: Extanded submission deadline from Nov. 15th to Nov. 22th, and accepted notification from Nov. 20th to Nov. 30th
  • 2023-10-22: Updated time schedule about submission deadline, paper review time and author notification time in page timeline
  • 2023-9-19: Updated submission deadline from Oct. 21th to Nov. 22th, and notification date from Nov. 15th to Nov. 30th
  • 2023-09-15: Added WeChat QRCode contact method in contact page

Accepted abstract & Full paper will be invited to give the presentation at ICCWAMTIP 2024

+ Email: icacia@uestc.edu.cn

Our Links

diff --git a/speakers.html b/speakers.html index 123c01b..a4e3642 100644 --- a/speakers.html +++ b/speakers.html @@ -16,4 +16,4 @@ footer[data-v-e541b38c]{background-color:#19181d;color:#b2b1b8}.title[data-v-e54

Accepted abstract & Full paper will be invited to give the presentation at ICCWAMTIP 2024

+ Email: icacia@uestc.edu.cn

Our Links

diff --git a/timeline.html b/timeline.html index 1108731..d221455 100644 --- a/timeline.html +++ b/timeline.html @@ -8,4 +8,4 @@ footer[data-v-e541b38c]{background-color:#19181d;color:#b2b1b8}.title[data-v-e54

Call for paper

Paper format

Conference Timeline

Event Schedule (China Standard Time, UTC+08:00)
Submission Deadline : Nov. 22th
Paper Review From Oct. 30th to Nov. 30th
Author Notification From Nov. 20th to Nov. 30th
Camera Ready Submission & Payment Deadline : Dec. 3th
Conference From Dec. 14th to Dec. 16th

Accepted abstract & Full paper will be invited to give the presentation at ICCWAMTIP 2024

+ Email: icacia@uestc.edu.cn

Our Links

diff --git a/topics.html b/topics.html index 9c7c3aa..4da7187 100644 --- a/topics.html +++ b/topics.html @@ -8,4 +8,4 @@ footer[data-v-e541b38c]{background-color:#19181d;color:#b2b1b8}.title[data-v-e54

Call for paper

Paper format

Topic

The topics of the conference include and not only include:

  1. Theory and Experiment

    • Fractal geometry

    • Wavelet algorithm and multi-wavelet

    • Signal processing

    • Microwave

    • Data mining and knowledge discovery

    • Blockchain technology

    • Machine learning & Deep learning

    • Intelligent communication systems

    • Intelligent algorithms and applications

    • Intelligent mechatronics

    • Neural networks, fuzzy systems and soft computing algorithms

    • Information and cyberspace security

    • Data privacy

    • Biomimetics and bio-inspired systems

    • Cancer Diagnostic Analysis

    • Computer network and internet modeling

    • Parallel, distributed computing

    • Big Data and Cloud Computing

    • Computational dynamical systems

  2. Multimedia Technology

    • Active media technology

    • Medical information

    • Vision and image processing

  3. Embedded System and Others

    • Traffic modeling and congestion control

    • System modeling, identification and simulation

    • Intelligent and biological control systems

    • System control and optimal control

    • Power system analysis and control

    • Adaptive and learning control

    • Process control and industrial automation

    • Feedback and decentralized control

    • Collaborative control systems

    • Robotics and intelligent vehicles

    • Hybrid control and hybrid dynamical systems

    • Tele-robotics, haptics, and tele-operated systems

    • Each layer Design for cognitive radio networks

    • Spectrum sharing and cognitive networking

    • Spectrum sensing

    • Sensing and perception

    • Applications of game theory in cognitive radio networks

    • Anti-interference Techniques for cognitive radio networks

    • Tracking, Telemetering and Command

    • Sensor networks

    • Sensors based control and automation

    • Sensor design, integration and fusion

    • Sensor data analysis and system diagnosis

    • Multi-agent systems and applications

    • Service science, management and engineering

    • Military-civilian integration

Accepted abstract & Full paper will be invited to give the presentation at ICCWAMTIP 2024

+ Email: icacia@uestc.edu.cn

Our Links