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ASENS 2027: International Conference on Algorithms, Software Engineering and Network Security

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ASENS
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截稿日期:
2027-01-15 还有 123 天
通知日期:
会议日期:
2027-03-26
会议地点:
Xi an, China
届数:
浏览: 7703   关注: 1   参加: 0

会伴指数 (CP-I)

46.4 / 100
全站第 2,440 名 / 共 5,682 个会议 · 前 43%

理论与算法 第 91 / 142 软件工程 第 150 / 247 安全与隐私 第 154 / 360

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%)
43
社区关注 (10%)
20
资料公开度 (15%)
55

用到的输入: 有据可查的届次：4 · 在会伴关注它的研究者：1 人 · 过去 24 个月打开过本页的研究者：5 人

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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 1.1 · 算于 2026-09-14

征稿

ASENS 2027 (International Conference on Algorithms, Software Engineering and Network Security) is an academic conference held in Xi an, China on 2027-03-26. The paper submission deadline is 2027-01-15.

The topics of interest for submission include, but are not limited to: Computational Intelligence Frontiers in Computational Intelligence and its Applications; Advances in Computational Intelligence for Optimization Challenges; Computational Intelligence in Dynamic and Uncertain Environments; Evolutionary Computation for Complex Problem Solving; Evolutionary Computation and Learning; Natural Computing; Evolutionary Dynamic Optimization Software Engineering AI for Software Engineering; Software Engineering for AI; Software Analytics; Maintenance and Evolution; Human and Social Aspects; Requirements and Modeling; Testing and Analysis; Architecture and Design; Dependability and Security; Tools and Processes Machine Learning Transfer Learning; Graph Learning; Causal Inference; Multi-view Learning; Stream Learning; Reinforcement Learning; Large Language Model; Deep Learning; Robust Learning; Online Learning; Continual Learning Cybersecurity Content-based network security; Industrial internet of things; AI-generated content security; Data security; Cryptography and its applications; Artificial intelligence security; Blockchain-based data sharing across domains; Trusted data exchange; Cyberspace security; Knowledge representation and discovery; Intelligent systems; Data security and privacy; Network attack and defense; Situation awareness Big Data Novel algorithms and techniques for data mining and big data analytics; Development, applications, and challenges of big models; Integration of machine learning and AI with big data; Data ethics, privacy, and security concerns in big models; Case studies and applications of big data across various industries; Scalability and efficiency challenges in big data systems; Visualization and interpretability of big models; The future of AI and big data in the post-digital era Computer Vision Image and Video Synthesis; Machine Learning and Deep Learning for Images and Video; Image and Video Analysis; Motion Estimation, Registration, and Fusion; Biomedical Image Processing; Computer Vision for Robotics; Augmented Reality and Virtual Reality Applications; 3D Computer Vision; Vision for Autonomous Vehicles
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