会議情報

NCAA 2021: International Conference on Neural Computing for Advanced Applications

会議のウェブサイトを表示するにはログインしてください
無料登録で公式サイトの閲覧、締切のトラッキング、メールリマインダーが利用できます。
ログイン 新規登録

投稿締切日:
2021-04-05 Extended
通知日:
2021-05-16
開催日:
2021-08-27
開催地:
Guangzhou, China
閲覧: 14047   フォロー: 1   参加: 0

論文募集

NCAA 2021 (International Conference on Neural Computing for Advanced Applications) is an academic conference held in Guangzhou, China on 2021-08-27. The paper submission deadline is 2021-04-05 (extended). Acceptance notifications are sent on 2021-05-16.

NCAA is an annual international neural computing conference, which showcases state-of-the-art R&D activities in neural computing systems and their industrial and engineering applications. It provides a forum for technical presentations and discussions among neural computing researchers, developers and users from academia, business and industry. The 2021 NCAA will be held in Guangzhou, China on July 2-5, 2021. China, a country which has a long history of 5000 years, is the perfect venue for addressing contemporary neural computing issues as new AI-related technical trends have been arising out of China’s top-notch IT infrastructure and cultural dynamicity. Guangzhou, also known as Canton and formerly romanized as Kwangchow, is the capital and most populous city of the province of Guangdong in southern China. On the Pearl River about 120 km (75 mi) north-northwest of Hong Kong and 145 km (90 mi) north of Macau, Guangzhou has a history of over 2,200 years and was a major terminus of the maritime Silk Road, and continues to serve as a major port and transportation hub, as well as one of China’s three largest cities. Due to a high urban population and large volumes of port traffic, Guangzhou is a Large-Port Megacity, the largest type of port-city in the world. For up-to-date information on NCAA2021, visit its homepage: https://dl2link.com/ncaa2021 For more information about Guangzhou, see https://dl2link.com/ncaa2021/travel/aboutGuangzhou TOPICS of interest are relevant to building practical systems are within its scope, including but not limited to: applicable neural networks theory applied statistics artificial intelligence computer vision control theory and systems data mining data security and privacy protection evolutionary computing fuzzy logic fault diagnosis hardware implementations hybrid intelligent systems image processing and understanding intelligent agents intelligent forecasting machine learning natural language processing neural networks neuro-fuzzy systems nn-based industrial applications pattern recognition self-learning systems software simulations supervised and unsupervised learning methods system engineering and integration
最終更新：Dou Sun（）

関連会議

CCFCOREQUALIS略称正式名称投稿締切通知日開催日
aa*a1SIGIRInternational Conference on Research and Development in Information Retrieval2026-01-152026-04-022026-07-20
aa*a1AAAIAAAI Conference on Artificial Intelligence2026-07-212026-11-302027-02-16
aa*a1CVPRIEEE Conference on Computer Vision and Pattern Recognition2025-11-062026-02-202026-06-03
bba1ICRAInternational Conference on Robotics and Automation2025-09-152026-06-01
aa*a1IJCAIInternational Joint Conference on Artificial Intelligence2026-01-312026-08-15
aa*a1STOCACM Symposium on Theory of Computing2025-11-042026-02-012026-06-22
cba2ICCInternational Conference on Communications2025-10-132026-01-122026-05-24
caa2IJCNNInternational Joint Conference on Neural Networks2025-01-152025-03-312025-06-30
bba1ICASSPInternational Conference on Acoustics, Speech and Signal Processing2026-09-162027-01-132027-05-16
ba*a1PODSACM SIGMOD Conference on Principles of DB Systems2026-12-032027-03-012027-06-13

関連ジャーナル

CCF正式名称インパクトファクター出版社ISSN
bNeural Networks6.3Elsevier0893-6080
bIEEE Transactions on Multimedia9.7IEEE1520-9210
cKnowledge-Based Systems7.2Elsevier0950-7051
bSoftware & Systems Modeling3.2Springer1619-1366
aIEEE Transactions on Computers3.8IEEE0018-9340
cFuture Generation Computer Systems6.1Elsevier0167-739X
cNeurocomputing6.5Elsevier0925-2312
cPattern Recognition Letters3.9Elsevier0167-8655
bPattern Recognition7.6Elsevier0031-3203
IEEE Access3.6IEEE2169-3536

コメント 0

まだコメントはありません。

コメントするにはログインしてください

広告