Reliable and Data-driven AI Applications in Edge-Cloud Environments

被引：0

作者：

Ko, In-Young ^{[1
]}

Mrissa, Michael ^{[2
,3
]}

Srivastava, Abhishek ^{[4
]}

机构：

[1] Korea Adv Inst Sci & Technol, Sch Comp, Daejeon, South Korea

[2] Univ Primorska, InnoRenew CoE, Koper, Slovenia

[3] Univ Primorska, Fac Math Nat Sci & Informat Technol, Koper, Slovenia

[4] Indian Inst Technol Indore, Dept Comp Sci & Engn, Indore, India

来源：

FRONTIERS OF COMPUTER VISION, IW-FCV 2024 | 2024年 / 2143卷

关键词：

Edge cloud; Big data; Machine learning; AI applications;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

To maximize the benefit of using edge-cloud environments, it is necessary to define new Web engineering paradigms and practices to make data-driven edge-cloud AI applications more efficient and reliable. The second international workshop on Big data-driven Edge Cloud Services (BECS 2022) was held to provide a venue in which scholars and practitioners can share their experiences and present ongoing work on providing reliable and efficient Web services for users by utilizing big data in edge cloud environments.

引用

页码：2 / 4

页数：3