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pro vyhledávání: '"Gorlatova, Maria"'
Virtual content instability caused by device pose tracking error remains a prevalent issue in markerless augmented reality (AR), especially on smartphones and tablets. However, when examining environments which will host AR experiences, it is challen
Externí odkaz:
http://arxiv.org/abs/2308.16813
PrivaScissors: Enhance the Privacy of Collaborative Inference through the Lens of Mutual Information
Edge-cloud collaborative inference empowers resource-limited IoT devices to support deep learning applications without disclosing their raw data to the cloud server, thus preserving privacy. Nevertheless, prior research has shown that collaborative i
Externí odkaz:
http://arxiv.org/abs/2306.07973
Next-generation augmented reality (AR) promises a high degree of context-awareness - a detailed knowledge of the environmental, user, social and system conditions in which an AR experience takes place. This will facilitate both the closer integration
Externí odkaz:
http://arxiv.org/abs/2303.12968
Edge computing is increasingly proposed as a solution for reducing resource consumption of mobile devices running simultaneous localization and mapping (SLAM) algorithms, with most edge-assisted SLAM systems assuming the communication resources betwe
Externí odkaz:
http://arxiv.org/abs/2301.04620
The importance of the dynamics of the viewport pose, i.e., the location and the orientation of users' points of view, for virtual reality (VR) experiences calls for the development of VR viewport pose models. In this paper, informed by our experiment
Externí odkaz:
http://arxiv.org/abs/2201.04060
Markerless augmented reality (AR) has the potential to provide engaging experiences and improve outcomes across a wide variety of industries; the overlaying of virtual content, or holograms, onto a view of the real world without the need for predefin
Externí odkaz:
http://arxiv.org/abs/2109.14757
We investigate training machine learning (ML) models across a set of geo-distributed, resource-constrained clusters of devices through unmanned aerial vehicles (UAV) swarms. The presence of time-varying data heterogeneity and computational resource i
Externí odkaz:
http://arxiv.org/abs/2106.15734
Fog computing, which distributes computing resources to multiple locations between the Internet of Things (IoT) devices and the cloud, is attracting considerable attention from academia and industry. Yet, despite the excitement about the potential of
Externí odkaz:
http://arxiv.org/abs/1811.02638
This paper introduces an analytical framework to investigate optimal design choices for the placement of virtual controllers along the cloud-to-things continuum. The main application scenarios include low-latency cyber-physical systems in which real-
Externí odkaz:
http://arxiv.org/abs/1712.00100
Autor:
Gorlatova, Maria
Recent advances in ultra-low-power wireless communications and in energy harvesting will soon enable energetically self-sustainable wireless devices. Networks of such devices will serve as building blocks for different Internet of Things (IoT) applic