会议信息

CTCNet 2026: Asia Pacific Conference on Computing Technologies, Communications and Networking

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截稿日期:
2026-10-25 已截稿
通知日期:
2026-11-25
会议日期:
2026-12-25
会议地点:
Xiamen, China
届数:
浏览: 12981   关注: 3   参加: 0
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CTCNet
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会伴指数 (CP-I)

46.4 / 100
全站第 2,588 名 / 共 5,761 个会议 · 前 45%

网络与通信 第 394 / 874

学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
37
社区关注 (10%)
31
资料公开度 (15%)
55

用到的输入: 有据可查的届次：3 · 在会伴关注它的研究者：3 人 · 过去 24 个月打开过本页的研究者：10 人

公开资料里还缺: 历年录用率 (+4.5) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 45% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.2 · 算于 2026-10-28

征稿

CTCNet 2026 (Asia Pacific Conference on Computing Technologies, Communications and Networking) is an academic conference held in Xiamen, China on 2026-12-25. The paper submission deadline is 2026-10-25. Acceptance notifications are sent on 2026-11-25.

The aim of this conference is to provide a platform for researchers, engineers, academicians as well as industrial professionals from all over the world to present their research results in various topics of Computing Technologies, Communications and Networking. It provides participants an opportunity to discuss the recent developments in the fields of computer science and its related areas. Original papers are invited to submit to the following Track areas: Track 1: Advanced Computing Paradigms and Intelligent Systems Cloud, edge, fog, and serverless computing architectures High-performance, parallel, and distributed computing Quantum computing and novel computational models AI/ML platforms, MLOps, and large-scale model deployment Green computing, energy-efficient algorithms, and sustainable ICT Virtualization, containerization, and orchestration (e.g., Kubernetes) Operating systems, middleware, and system software for next-generation computing Track 2: Wireless Communications and Next-Generation Networks 5G/6G network architectures, protocols, and radio access technologies Massive MIMO, beamforming, channel modeling, and propagation mmWave, Terahertz, and visible light communications Cognitive radio, dynamic spectrum access, and spectrum sharing Device-to-device (D2D), vehicle-to-everything (V2X), and machine-type communications (mMTC) Non-terrestrial networks (satellite, UAV, HAPS) and integrated space-terrestrial systems Optical fiber, free-space optical, and photonic technologies (as enabling tools for communication) Track 3: Network Architectures, Security, and Management Software-defined networking (SDN), network function virtualization (NFV), and network slicing Intent-based networking, autonomic network management, and AI-driven network operations Future Internet architectures (e.g., information-centric networking, named data networking) Cybersecurity, zero-trust architectures, intrusion detection, and blockchain for networking Network resilience, fault tolerance, quality of service (QoS), and quality of experience (QoE) Traffic engineering, network optimization, and resource allocation Edge/fog networking and integrated cloud-edge continuum Track 4: Signal Processing, Multimedia, and Data Analytics Digital signal processing for communications, sensing, and control Image, video, and audio coding, compression, and streaming Multimedia content delivery, adaptive bitrate, and content distribution networks Speech/audio processing, acoustic scene analysis, and related applications Machine learning and deep learning for signal processing (e.g., channel estimation, detection, denoising) Signal processing for IoT, sensor networks, and cyber-physical systems Data fusion, big data analytics, and visualization techniques Track 5: Emerging Applications, AI-empowered Services, and Interdisciplinary Innovations Smart cities, smart grids, intelligent transportation, and industrial IoT (IIoT) Edge AI, distributed intelligence, and real-time analytics for vertical industries Augmented reality (AR), virtual reality (VR), mixed reality (MR), and metaverse applications Drone/UAV networks, swarm robotics, and autonomous systems Digital twins, simulation, and model-based systems engineering Social network analysis, recommender systems, and data-driven services Green ICT, sustainable networking, and environmental impact reduction
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