… These works consider object classification as the primary vision workload, which is in
contrast to our envisioned scenario here: mobile vision applications piggybacked on local GPU …

… to all the real-time edge vision applications that we describe in Section II-A. … -time edge
vision applications, rending the per frame latency around 32ms. Our study shows that edge cloud …

… visual sensors (cameras) and the cloud/edge servers do not always provide sufficient
and … , an edge-to-cloud framework for advanced vision analytics that co-designs the cloud-side …

… CSS and edge device. In this article, we discuss the advantages of edge computing over
cloud computing to overcome latency and reliability issues in critical applications. Moreover, the …

… Instead, we will discuss three types of future IoT applications could directly benefit from
the edge cloud vision we discussed above. Moreover, since currently the key enabling …

… from various computer visions applications such as motion … In this paper, we propose a
cloud platform that integrates the … integrated and configured in the cloud application. Thus, the …

… devices are often incapable of executing complex vision algorithms with low latency and …
of both cloud-only and edge-only solutions, we present SurveilEdge, a collaborative cloud-edge …

… design a intelligent edge computing cloud based on 5G scheme. In the ends, an vision detection
… visual detection application scene design its feasibility purpose in the wireless network. …

… a cloud-edge collaboration … the edge server and a deep model (ie, CloudCNN) on the cloud
server. EdgeCNN can provide durable and rapid response cognitive services, because edge …

… any application demands) to edge-computing and IoT devices (to sense and act on the real
world). This paper presents the Cloud … as a full chipto-Cloud solution. Focusing on a smart …