One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...
We propose a new methodology for fusing temporally changing multisensor raster and vector data by developing a spatially and temporally varying uncertainty model of acquired and t...
We present an interactive system for generating photorealistic, textured, piecewise-planar 3D models of architectural structures and urban scenes from unordered sets of photograph...
Sudipta N. Sinha, Drew Steedly, Richard Szeliski, ...
Abstract— This paper describes an efficient method for retrieving the 3-dimensional shape associated to novelties in the environment of an autonomous robot, which is equipped wi...
This paper discusses a model-based design flow for requirements in distributed embedded software development. Such requirements are specified using a language similar to Linear T...
Luciano Lavagno, Marco Di Natale, Alberto Ferrari,...