NIMBUS：一种用于交互领域视觉学习的混合云-群实时架构
NIMBUS: A Hybrid Cloud-Crowd Realtime Architecture for Visual Learning in Interactive Domains
摘要：
整合基于云的资源的机器人架构刚刚开始流行。然而，研究人员很少调查他们的能力，以支持他们的可行性索赔。我们提出了一种新的方法来交换响应速度的质量。此外，我们支持这一论断与亚马逊机械土耳其人进行的实验的实证研究结果，并发现我们的方法提高了质量，以换取我们的认知架构中的响应时间。
英文摘要：
Robotic architectures that incorporate cloud-based resources are just now gaining popularity. However, researchers have very few investigations into their capabilities to support claims of their feasibility. We propose a novel method to exchange quality for speed of response. Further, we back this assertion with empirical findings from experiments performed with Amazon Mechanical Turk and find that our method improves quality in exchange for response time in our cognitive architecture.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
