Abstract:
Provided are a method and apparatus for interpolating X-ray tomographic image data by using a machine learning model. A method of interpolating an X-ray tomographic image or X-ray tomographic composite image data includes obtaining a trained model parameter via machine learning that uses a sub-sampled sinogram for learning as an input and uses a full-sampled sinogram for learning as a ground truth; radiating X-rays onto an object at a plurality of preset angular locations via an X-ray source, and obtaining a sparsely-sampled sinogram including X-ray projection data obtained via X-rays detected at the plurality of preset angular locations; applying the trained model parameter to the sparsely-sampled sinogram by using the machine learning model; and generating a densely-sampled sinogram by estimating X-ray projection data not obtained with respect to the object on the sparsely-sampled sinogram.
Abstract:
A cleaning robot is provided. The cleaning robot includes a main body, a moving assembly to move the main body around a home, an imaging unit to obtain images around the main body, a controller to generate a map of the home using the obtained images, and a communication unit to transmit the generated map to a home monitoring apparatus. A procedure to match location and type information of electric devices to a two-Dimensional (2D) or three-Dimensional (3D) map of the home may be automated. As described above, the map of the home may be realistically generated by utilizing a map generated by the cleaning robot and inconvenience experienced by a user to manually register electric devices located in each room of the home may be solved by automatically registering the electric devices.