Información de la conferencia

EIBDCT 2026: International Conference on Electronic Information Engineering, Big Data and Computer Technology

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Día de Entrega:
2026-02-07
Fecha de Notificación:
Fecha de conferencia:
2026-04-24
Ubicación:
Haikou, China
Ediciones:
5
Vistas: 10887   Seguidores: 3   Asistentes: 0

Solicitud de Artículos

EIBDCT 2026 (International Conference on Electronic Information Engineering, Big Data and Computer Technology) is an academic conference held in Haikou, China on 2026-04-24. The paper submission deadline is 2026-02-07.

2026 5th International Conference on Electronic Information Engineering, Big Data and Computer Technology provides a premier forum for the presentation of new advances and research results in the fields of Electronic Information Engineering, Big Data and Computer Technology. The conference will bring together leading researchers, social workers and scientists in the domain of interest from around the world. The topics of interest for submission include, but are not limited to: ◕ Information Science and Applied technology · Security and cryptography · System security · bioinformatics · Bioinformatics and scientific computing · Multimedia application · Expert system · Human-computer interaction · Information retrieval · Information system · Computer architecture and embedded systems · Computer security · Mobile application · Multimedia application ◕ Information Network and big Data · Wireless communication and mobile computing · Wireless sensor network · Internet of Things · Web 2.0 technology · Social networking and marketing · Satellite network · Digital twin · Integrated sensing, computing and storage · Wireless communication · Internet and web applications · 5G and above networks · B5G+ Industrial Internet · Data center network · Data mining · Knowledge engineering · Data compression ◕ Machine Learning and Neural Networks in Communication Systems · Machine Learning for Wireless Communication and 5G Networks · AI-based Optimization and Resource Allocation in Communication Networks · Deep Learning for Signal Processing, Channel Estimation, and Spectrum Management · Cognitive Radio Networks and Machine Learning for Dynamic Spectrum Access · Neural Networks for MIMO Systems, Beamforming, and Network Security · Machine Learning for Network Traffic Prediction and Intrusion Detection · AI Techniques for Quality of Service (QoS) and Quality of Experience (QoE) in Networks · Data-driven Approaches for IoT and Autonomous Communication Systems · Deep Reinforcement Learning for Communication Network Optimization
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