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MLICOM 2026: EAI International Conference on Machine Learning and Intelligent Communications

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投稿締切日:
2026-08-31 締切済み
通知日:
2026-09-20
開催日:
2026-11-07
開催地:
Sanya, China
開催回数:
閲覧: 16586   フォロー: 0   参加: 0
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MLICOM
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会伴インデックス (CP-I)

49.4 / 100
全 5,721 件中 第 1,812 位 · 上位 32%

人工知能・機械学習 分野 743 件中 第 189 位 ネットワーク・通信 分野 868 件中 第 261 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%)
62
コミュニティの注目度 (10%)
12
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：9 · 過去 24 か月にこのページを開いた研究者：4 人

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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 1.2 · 算出日 2026-10-19

論文募集

MLICOM 2026 (EAI International Conference on Machine Learning and Intelligent Communications) is an academic conference held in Sanya, China on 2026-11-07. The paper submission deadline is 2026-08-31. Acceptance notifications are sent on 2026-09-20.

Scope Emerging artificial intelligence (AI) and machine learning (ML) technologies, coupled with advanced intelligent communications, are driving a paradigm shift across academic research and industrial applications. From multi-modality learning to federated intelligence, these technologies are not only revolutionizing wireless communication systems (e.g., physical layer optimization, intelligent decision-making, and secure data transmission) but also enabling deep integration with diverse fields such as healthcare, industry, manufacturing, education, culture, governance, and digital humanities. The integration of ML and intelligent communications breaks through traditional domain boundaries—for instance, realizing secure transmission of medical data via federated learning, optimizing industrial IoT communication for smart manufacturing, and facilitating cross-cultural humanistic exchange through intelligent language processing. MLICOM 2026 aims to build a comprehensive academic platform that bridges ML/AI algorithms, intelligent communication technologies, and cross-domain applications. We welcome high-quality original research papers (theoretical, experimental, or application-oriented) focusing on recent advancements, challenges, and innovative solutions at the intersection of ML and intelligent communications. By covering a broad spectrum of fields including digital humanities, the conference seeks to foster interdisciplinary dialogue among academia, industry, and public sectors, and serve as a catalyst for the development of next-generation intelligent communication systems and their practical deployments. Topics 1. ML & Intelligent Communications Foundations Intelligent cloud / edge / cloud-edge collaborative communications ML-driven resource allocation (spectrum, power, computation, bandwidth) Green and energy-aware intelligent communications (sustainable network design) Intelligent software-defined radios (SDR) and flexible communication architectures Intelligent massive MIMO, beamforming, and dynamic antenna configuration Cooperative and distributed coding & signal processing for intelligent networks Wireless sensor networks (WSN) and IoT: ML-optimized data transmission Satellite and radar communications: intelligent signal processing and anti-interference Cognitive radio networks: ML-based spectrum sensing and sharing Federated learning (FL) and distributed learning for secure communication systems Multi-modality learning for cross-media communication (text, image, audio, video) Pre-trained models and transfer learning in intelligent communications Generative AI for communication content generation and error correction ML-driven network security, privacy preservation, and trust management 2. Cross-Domain Applications of ML 2.1 Industry & Manufacturing Industrial IoT (IIoT) communication optimization for smart factories ML-driven predictive maintenance via real-time industrial data transmission Intelligent communication in collaborative robotics and automated production lines 2.2 Education & E-Learning Intelligent remote teaching communication platforms (adaptive bandwidth allocation) ML-based personalized learning: communication optimization for educational data Secure transmission of educational big data and cross-institutional collaboration AI-driven interactive communication tools 2.3 Government & Public Services Smart governance communication platforms Secure communication for e-government AI-driven traffic and transportation communication Environmental monitoring: ML-based communication for sensor networks 2.4 Other Emerging Applications Intelligent unmanned systems (vehicles, drones): communication and adaptive sensing Accessible communication: ML-optimized solutions for people with disabilities ML-based semantic communication and cultural adaptation Digital archaeology: communication optimization for remote sensing data AI-assisted preservation of endangered languages: intelligent speech and text communication ML-based analysis of humanistic communication patterns 3. Other Relevant Topics Datasets and evaluation metrics for ML-empowered intelligent communications Low-resource language processing in cross-lingual communication Edge AI for resource-constrained communication devices Quantum machine learning for next-generation secure communications Ethical and regulatory issues of AI-driven intelligent communications
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