Nokia Solutions and Networks Oy

Aimotive Kft.

Csaba Mate Jozsa

Gábor Sörös

Lóránt Farkas

Richárd Zsámboki

Szabolcs Vajna

Daniel Akos Kozma

Daniel Szolgay

Disclosed is a method comprising: creating a first structure graph whose nodes represent points of a first structure map, the nodes being associated with state vectors obtained using feature vectors of the points of the first structure map; creating a first RF graph having nodes representing points of a respective first RF map; creating a first input graph from the first structure graph and the first RF graph; updating state vectors of the nodes of the first input graph; creating an output graph whose nodes represent target spatial points of the environment; connecting the output graph with at least the first input graph; updating the state vectors of the output graph; inputting the state vectors of the output graph to a trained machine learning model to obtain a prediction of a signal propagation characteristic at the target points.

Radio signal prediction in an environment

Methods, systems, and computer program products for lane detection. An image processing module is trained by machine learning, and used to generate correspondence mapping data based on an image pair of a first and second images. The correspondence mapping data defines correspondence between a first lane boundary group of the first image and a second lane boundary group of the second image. An image space data block of image space detection pairs is then generated based on the correspondence mapping data, and a three-dimensional lane detection data block generated using triangulation based on first and second parts of the image space data block corresponding to respective first and second members of the image space detection pairs.

Method and system for lane detection

Growing community of inventors

Budapest, Hungary

Csaba Mate Jozsa