IEEE SMC Hiroshima Chapter 会員各位：

#重複して受け取られた場合はご容赦ください．

　　　　　　　　　　　　　　　IEEE SMC Hiroshima Chapter

　　　　　　　　　　　　　　　Chair　林田　智弘（広島大学）

日頃からIEEE SMC Hiroshima Chapterの活動にご協力いただきありがとうございます．

国際会議IEEE SMC2019の投稿締め切り再々延長についてご案内いたします．

IEEE SMC2019は10月6日～9日にかけて，イタリアのBariで開催されます．

IEEE SMC Hiroshima Chapterでは，県立広島大の市村先生と広島市立大学の原先生および

私がオーガナイザーとして，

Special Session on "Innovative Computational Intelligence and Real‐World Applications"

を企画しています．

この度，投稿締切が，

April 28, 2019

まで再度延長されました．こちらは[Firm Deadline] となっております．

引き続き，ご投稿を検討いただければ幸いです．

本Special Sessionにご投稿いただける場合は，下記のSpecial Sessionページ中の

[IEEE SMC2019]のリンクから，[Special Session Papers]を選択して

ご投稿いただきますようお願いします．

http://conf.papercept.net/conferences/scripts/start.pl

なお，ご投稿の際には，Special Session Code

57b9k

をご入力ください．

皆様のご投稿をお待ちしております．

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　　　　　IEEE SMC2019 Special Session Call for Papers

October 6-9, 2019

Bari, Italy

IEEE SMC2019 Special Session on

"Innovative Computational Intelligence and Real‐World Applications"

Special Session Code: 57b9k

Co-organizers: Tomohiro Hayashida (Hiroshima Univ.)

               Akira Hara (Hiroshima City Univ.)

               Takumi Ichimura (Prefectural Univ. of Hiroshima) (Organized by IEEE SMC HIROSHIMA CHAPTER)

Web site:

http://www.smc2019.org/

http://conf.papercept.net/conferences/scripts/start.pl

[Abstract]

Computational Intelligence technologies have made great progress in recent decades. Real-world environments produce big data, which is large-scale, high-dimensional, multi-modal, sequential and ambiguous data. Since many real-world problems are not considered to be well-posed mathematically, attempts of analytic approaches to find solutions met some difficulties. For dealing with such complex data, various techniques are required such as visualization by clustering of multi-modal and sequential data, automatic feature extraction by representation learning, acquisition of comprehensible knowledge from learning results and so on. Driven by such motivation, emerging computational intelligence approaches have been proposed in the soft computing areas like artificial neural networks, evolutionary computation and fuzzy theories. As one of the successes, Deep Learning is now becoming popular in the field of computer science. According to the brisk activities, many researchers also have been able to challenge solving industrial problems. We discuss in this session the computational intelligence technologies for learning real world complex data, which will make an explicit or implicit knowledge to the real-world problems that prior technologies cannot provide satisfactory solutions. This session is organized by IEEE SMC Hiroshima Chapter.

[Keywords]

Big Data Analytics

Computational Intelligence

Evolutionary Computation

Fuzzy Systems and Applications

Knowledge Acquisition in Intelligent Machine Leaning

Medical Informatics

Neural Networks and Applications

Optimization

Swarm Intelligence

[Important Dates]

April 28, 2019: Paper submission due (Firm Deadline)

June 7, 2019: Notification of Acceptance

July 7, 2019: Early registration deadline

July 7, 2019: Camera-ready deadline

[Contact]

Prof. Tomohiro Hayashida (Hiroshima University) hayashida@hiroshima-u.ac.jp