LiteRT.js runs machine learning models locally with CPU, GPU and emerging NPU acceleration, potentially reducing server infrastructure, inference charges and data movement.
Abstract: The widespread use of radio maps has provided a seamless locating solution for urban users. However, the spatial ambiguity of received signal strength (RSS), influenced by the urban ...
Abstract: Most of today’s simultaneous localization and mapping (SLAM) approaches learn the map of the environment in the first stage (referred to as mapping) and subsequently use this static map for ...
LoD-Loc tackles visual localization w.r.t a scene represented as LoD 3D map. Given a query image and its pose prior, the method utilizes the wireframe of LoD models to recover the camera pose. This ...
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