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SoICT 2026: International Symposium on Information and Communication Technology

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SoICT
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投稿締切日:
2026-09-09
通知日:
2026-10-12
開催日:
2026-12-04
開催地:
Ho Chi Minh City, Vietnam
開催回数:
閲覧: 23871   フォロー: 4   参加: 1

会伴インデックス (CP-I)

53.6 / 100
全 5,683 件中 第 976 位 · 上位 18%

ネットワーク・通信 分野 864 件中 第 134 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%)
75
コミュニティの注目度 (10%)
29
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：15 · 会伴でフォローしている研究者：4 人 · 過去 24 か月にこのページを開いた研究者：5 人

公開情報で不足しているもの: 過去の採択率 (+4.5) · 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 2026-09-21

論文募集

SoICT 2026 (International Symposium on Information and Communication Technology) is an academic conference held in Ho Chi Minh City, Vietnam on 2026-12-04. The paper submission deadline is 2026-09-09. Acceptance notifications are sent on 2026-10-12.

CONFERENCE SCOPES Relevant topics include, but are not limited to: Applied AI, Big Data Analytics, and Data-Driven Applications This track focuses on applied artificial intelligence, big data analytics, and data-driven solutions for real-world problems. It welcomes research contributions, system designs, industrial applications, and case studies that demonstrate how AI, machine learning, data mining, and large-scale data analytics can be used to improve decision-making, automation, prediction, optimization, and innovation across domains. The track emphasizes practical AI applications, data-driven methods, scalable analytics, and the deployment of AI-based solutions in industry, government, education, healthcare, finance, transportation, smart cities, agriculture, and other socio-economic sectors. Topics of interest include, but are not limited to: Applied machine learning and deep learning Big data analytics and large-scale data processing Data mining, knowledge discovery, and predictive analytics AI applications in industry, government, education, healthcare, finance, agriculture, and smart cities Decision support systems and intelligent analytics Data-driven optimization and intelligent decision-making AI for business intelligence and digital transformation Recommender systems and personalization Time-series forecasting and anomaly detection Graph analytics and knowledge graphs for applications Natural language processing applications AI-powered automation and intelligent assistants Data visualization and visual analytics Responsible, explainable, and trustworthy applied AI Evaluation and deployment of AI systems in real-world environments Multimedia Processing, Computer Vision, and Multimodal Intelligence This track covers theories, methods, systems, and applications in multimedia processing, computer vision, image and video analysis, speech and audio processing, and multimodal intelligence. It welcomes research on the representation, understanding, retrieval, generation, and interaction of multimedia data, including text, image, video, audio, sensor data, and multimodal streams. The track also encourages submissions related to emerging multimodal AI systems, vision-language models, multimedia retrieval, human-centered multimedia computing, and intelligent media applications. Topics of interest include, but are not limited to: Image, video, audio, and speech processing Computer vision and pattern recognition Object detection, tracking, recognition, and segmentation Image and video understanding 3D vision, scene reconstruction, and visual perception Multimedia information retrieval and recommendation Multimodal learning and multimodal representation Vision-language models and multimodal foundation models Generative models for image, video, audio, and multimedia content Human action recognition and behavior analysis Medical image analysis and biomedical multimedia processing Remote sensing image analysis Document image analysis and OCR systems Augmented reality, virtual reality, and mixed reality Multimedia security, privacy, watermarking, and forensics Lifelogging, event retrieval, and personal multimedia analytics Multimedia applications in education, healthcare, culture, tourism, and smart cities Communications, Networking, and Cybersecurity This track addresses advances in communication systems, networking technologies, the Internet of Things, cloud-edge infrastructures, distributed systems, and cybersecurity. It welcomes both theoretical and applied research on the design, optimization, management, and security of modern communication and networked systems. The track also covers emerging topics such as 5G/6G networks, software-defined networking, edge intelligence, secure IoT systems, cyber-physical systems, blockchain-enabled security, privacy-preserving technologies, and resilient digital infrastructures. Topics of interest include, but are not limited to: Communication systems and wireless communications 5G, 6G, and beyond networks Internet of Things and industrial IoT Sensor networks and cyber-physical systems Software-defined networking and network function virtualization Cloud, edge, and fog computing infrastructures Mobile and ubiquitous computing Network protocols, architectures, and performance evaluation Network optimization, resource allocation, and traffic engineering Distributed systems and decentralized architectures Blockchain and distributed ledger technologies Cybersecurity and network security Cryptography and applied security Privacy-preserving computing and secure data sharing Intrusion detection, malware analysis, and threat intelligence Security of IoT, cloud, edge, and mobile systems Digital identity, authentication, and access control Resilience, reliability, and trust in networked systems AI for networking and cybersecurity Security governance, risk management, and compliance AI Foundations, Foundation Models, and Generative AI This track focuses on the foundations, theories, algorithms, models, and emerging paradigms of artificial intelligence. It welcomes high-quality research on machine learning, deep learning, reasoning, optimization, foundation models, large language models, generative AI, agentic AI, trustworthy AI, and evaluation methodologies. The track aims to provide a forum for fundamental advances in AI, including both theoretical contributions and methodological innovations that can serve as foundations for future intelligent systems and applications. Topics of interest include, but are not limited to: Foundations of artificial intelligence and machine learning Deep learning theories, architectures, and algorithms Foundation models and large language models Generative AI and generative models Diffusion models, GANs, VAEs, and autoregressive models Large language model reasoning, planning, and tool use AI agents and multi-agent systems Reinforcement learning and decision-making Knowledge representation and reasoning Neuro-symbolic AI Causal learning and causal reasoning Optimization methods for AI and machine learning Self-supervised, semi-supervised, and few-shot learning Continual learning, transfer learning, and domain adaptation Explainable AI and interpretable machine learning Trustworthy, safe, fair, and responsible AI AI alignment, evaluation, and benchmarking Efficient AI, model compression, and small language models Federated learning and privacy-preserving machine learning AI robustness, uncertainty estimation, and out-of-distribution detection Software Engineering, Trusted Digital Platforms, and Smart Services This track covers software engineering methods, tools, processes, architectures, and technologies for building reliable, secure, scalable, and intelligent software systems, digital platforms, and smart services. It welcomes research on both traditional and AI-enhanced software engineering, including requirements engineering, software architecture, software testing, DevOps, DevSecOps, MLOps, software analytics, and software maintenance. The track also focuses on trusted digital platforms, data spaces, interoperable services, blockchain-enabled trust infrastructures, cloud-native systems, smart service ecosystems, and software infrastructures that support the digital economy. It particularly welcomes research on secure and scalable platforms for digital transformation in government, industry, finance, education, healthcare, logistics, smart cities, and society. Topics of interest include, but are not limited to: Software Engineering Requirements engineering and requirements reasoning Software architecture and design Software modeling and model-driven engineering Software testing, debugging, verification, and validation Program analysis and software verification Software maintenance, evolution, and reengineering Software quality, reliability, usability, and maintainability Empirical software engineering Mining software repositories and software analytics Human and social aspects of software engineering Agile software development and software project management DevOps, DevSecOps, MLOps, and AIOps Secure software engineering Software engineering for cloud-native and microservices systems Software engineering for AI-based systems AI-assisted software development Code generation, code review, bug fixing, and automated program repair LLMs and AI agents for software engineering tasks Trusted Digital Platforms, Data Spaces, and Digital Economy Digital platform architecture and engineering Trusted and secure digital platforms Platform ecosystems and digital service ecosystems Digital economy platforms and data-driven service ecosystems Cloud-native platforms and service-oriented architectures Microservices, APIs, and interoperability Data platforms, data spaces, data fabric, and interoperable data infrastructures Digital identity, eKYC, authentication, authorization, and trust services Digital public infrastructure and trusted data exchange frameworks Blockchain and distributed ledger technologies for digital trust Smart contracts, verifiable credentials, provenance, and trusted registries Tokenization, traceability, and auditability in digital platform ecosystems Privacy-preserving data sharing and secure data collaboration Platform security, compliance, and risk management Scalable and resilient software infrastructures Low-code/no-code platforms Digital twin platforms and cyber-physical service platforms Governance of digital platforms, data spaces, and digital services Smart Services, FinTech, and Digital Applications Smart services for government, education, healthcare, industry, finance, logistics, and smart cities FinTech platforms and digital financial services Open banking, digital payment, digital lending, InsurTech, RegTech, and SupTech systems Blockchain-enabled financial services and trusted transaction platforms Data-driven services for the digital economy Intelligent service engineering and service innovation AI-enabled digital services Human-centered digital services Personalized and adaptive services Service automation and intelligent workflows Service quality, reliability, and user experience Evaluation of digital platforms and smart services Sustainable and responsible digital service development Lifelogging, Event Retrieval, and Personal Data Analytics This track focuses on methods, systems, datasets, and applications for lifelogging, event retrieval, personal data analytics, and human-centered multimedia understanding. It welcomes research on the collection, representation, indexing, retrieval, analysis, and visualization of personal and multimodal data from wearable devices, mobile sensors, cameras, social media, and digital services. Topics: Lifelogging systems and applications, Event retrieval and event understanding, Personal data analytics and personal informatics, Egocentric vision and wearable data analysis, Multimodal lifelog retrieval, Human activity recognition, Personal knowledge graphs and memory augmentation, Context-aware and location-aware personal data analysis, Privacy, ethics, and security in personal data analytics, Evaluation benchmarks, datasets, and challenges for lifelog retrieval, Human-centered interfaces for personal data search and exploration Quantum Information Topics: Quantum error correction, Quantum communication, Quantum algorithms, Quantum cryptography, Quantum simulation, Fault-tolerant quantum computing, Intersection of quantum information and machine learning
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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
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CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
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