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CICom 2021: EAI International Conference on Computational Intelligence and Communications

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CICom
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投稿締切日:
2021-05-01
通知日:
2021-06-01
開催日:
2021-09-02
開催地:
Versailles, France
開催回数:
2
閲覧: 10834   フォロー: 0   参加: 0

会伴インデックス (CP-I)

38.0 / 100
全 5,682 件中 第 5,407 位 · 上位 96%

人工知能・機械学習 分野 739 件中 第 701 位 ネットワーク・通信 分野 864 件中 第 831 位

学術的評価 (35%) データなし — 中立の基準値 50 点として算入 —
投稿の選択性 (20%) データなし — 中立の基準値 50 点として算入 —
開催回数 (20%)
30
コミュニティの注目度 (10%)
8
公開情報の充実度 (15%)
25

使用した入力: 確認できる開催回数：2 · 過去 24 か月にこのページを開いた研究者：2 人

公開情報で不足しているもの: 過去の採択率 (+4.5) · 過去の開催回 (+3.0) · 最優秀論文の記録 (+2.3)
主催者は会議を認証申請したうえで、このページから直接追加できます。スコアは毎晩再計算されます。このスコアを上げるには

信頼度 45% — スコアのうち、中立の基準値ではなく実際に観測されたデータに基づく割合。 このスコアの算出方法 · ランキングを見る · アルゴリズム版 1.1 · 算出日 2026-09-20

論文募集

CICom 2021 (EAI International Conference on Computational Intelligence and Communications) is an academic conference held in Versailles, France on 2021-09-02. The paper submission deadline is 2021-05-01. Acceptance notifications are sent on 2021-06-01.

CiCOM 2021 will provide an opportunity to exchange innovative research on Computational Intelligence and Communications. Computational Intelligence makes use of biologically and linguistically motivated computational paradigms including neural networks, fuzzy logic systems, and evolutionary computation, as well as social reasoning, artificial life, ambient intelligence, deep learning, and the likes. New technologies in communications bring new application paradigms for healthcare, transportation, education, agriculture, and social networks. With the arrival of 5G and 6G networks technologies, we need to address new research challenges, including the tight integration of machine intelligence, efficient and reliable networking, interoperability, scalability and security. Track topics include, but are not limited to: Track 1: Computational Intelligence in Automation, Control, and Intelligent Transportation System Intelligent Decision Making and Support Adaptive and Optimal Control Model-Predictive Control Fuzzy Systems and Control Fuzzy Neural Systems and Control Hybrid Intelligent Control Object recognitions, traffic sign detection and recognition Multimodal intelligent transport systems & services Vehicle communications and connectivity Driver and traveller support systems Simulation and forecasting models Driver assistance and automation systems Driver state detection and monitoring Track 2: Computational Intelligence on Big Data, Internet of Things, and Smart Cities Efficient algorithms on processing and analysis of big data Extracting and understanding from distributed, diverse and large-scale data resources Visualisation of big data and visual data analytics Human-computer interaction and collaboration in big data Classification, Clustering, Regression Data mining from nonstationary and drifting environments Novel Architecture and Protocols of AI Integrated with IoT Security, Privacy, Access Control, & Trust Frameworks of IoT Resource Management Techniques of Using AI for IoT Control Schemes in IoT Smart Data Storage in IoT Track 3: Computational Intelligence on Wireless Communication Systems and Cyber Security Machine Learning for Networks Unmanned Aerial Vehicles Wireless Sensor Networks Network Virtualization Software Defined Networks | Blockchain and its security Waveforms and Radio Access Technologies Software Defined Radio Visible Light Communication (VLC) Radio Access Networks Intrusion/malware detection, prediction, and classification Sensor network security, web security, wireless and 4G, 5G media security Self-awareness, auto-defensiveness, self-reconfiguration, and self-healing networking paradigm Modelling adversarial behaviour for threat detection Cloud and virtualization security Track 4: Computational Intelligence on Human/Brain-omputer Interfaces & Image and Pattern Recognition Signal processing for Brain-Computer Interface (BCI) BCI Feature Extraction, Pattern Recognition, and Multiple modalities for BCI Invasive and non-invasive BCIs. Online and offline BCI applications Advances on Human-Computer Interfaces Feature ranking and weighting Feature selection, extraction, construction, and reduction Feature analysis on high-dimensional and large-scale data Evolutionary computation for feature analysis Information theory, statistics, mathematical modelling, etc., for feature analysis Feature analysis in classification, clustering, regression, image analysis, and other tasks Real-world applications of computational intelligence for feature analysis
最終更新：Dou Sun（）

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