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CSML 2027: International Conference on Computer Science and Machine Learning

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投稿締切日:
2026-11-14 残り 3 日 延長
通知日:
2026-12-12
開催日:
2027-01-23
開催地:
Zurich, Switzerland
開催回数:
主催者:
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会伴インデックス (CP-I)

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全 5,771 件中 第 2,503 位 · 上位 44%

人工知能・機械学習 分野 755 件中 第 277 位

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開催回数 (20%)
48
コミュニティの注目度 (10%)
13
公開情報の充実度 (15%)
55

使用した入力: 確認できる開催回数：5 · 過去 24 か月にこのページを開いた研究者：5 人

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論文募集

CSML 2027 (International Conference on Computer Science and Machine Learning) is an academic conference held in Zurich, Switzerland on 2027-01-23. The paper submission deadline is 2026-11-14 (extended). Acceptance notifications are sent on 2026-12-12.

5th International Conference on Computer Science and Machine Learning (CSML 2027) January 23 ~ 24, 2027, Zurich, Switzerland https://dnlp2027.org/csml/index Scope 5th International Conference on Computer Science and Machine Learning (CSML 2027) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Soft Computing and Applications. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. Authors are solicited to contribute to this conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to. Topics of interest include, but are not limited to, the following • Artificial Intelligence • Bayesian Network • Big Data • Bioinformatics • Computer Architecture and Real time Systems • Computer Vision • Database and Data Mining • Deep Learning • Dependable, reliable and autonomic computing • Distributed and parallel systems & algorithms • Embedded system and software • Internet of Things (IoT) • Learning in knowledge-intensive systems • Learning Methods and analysis • Learning Problems • Machine Learning Algorithms • Modelling and Simulation • Natural Language Processing (NLP) • Networking and Communications • Neural Networks • Parallel and Distributed Systems • Predictive Learning • Reinforcement Learning • Security , Cryptography , Blockchain • Signal /Image Processing/Multimedia • Software Engineering • Supervised Machine Learning • Unsupervised Machine Learning • Web and internet computing Paper Submission Authors are invited to submit papers through the conference Submission System by November 14, 2026. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by Computer Science Conference Proceedings (H index 46) in Computer Science & Information Technology (CS & IT) series (Confirmed). Selected papers from CSML 2027, after further revisions, will be published in the special issue of the following journal. • International Journal of Computer Science & Information Technology (IJCSIT) • International Journal on Natural Language Computing (IJNLC) • Advanced Computing: An International Journal (ACIJ) • International Journal of Computer Science, Engineering and Applications (IJCSEA) • International Journal of Advanced Information Technology (IJAIT) • International Journal of Soft Computing (IJSC) • International Journal of Artificial Intelligence & Applications (IJAIA) • Machine Learning and Applications: An International Journal (MLAIJ) • Information Technology in Industry (ITII) Important Dates • Submission Deadline : November 14, 2026 • Authors Notification : December 12, 2026 • Registration & camera - Ready Paper Due : December 19, 2026 Contact Us Here's where you can reach us: [email protected] (or) [email protected] Submission URL: https://aisca2027.org/submission/index.php
最終更新：Ronan Hugi （）

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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
BMachine Learning2.9Springer0885-6125
AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
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IEEE Access3.6IEEE2169-3536

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