US 12,243,283 B2
Device and method for determining a semantic segmentation and/or an instance segmentation of an image
Chaithanya Kumar Mummadi, Pittsburgh, PA (US); Jan Hendrik Metzen, Boeblingen (DE); and Robin Hutmacher, Renningen (DE)
Assigned to ROBERT BOSCH GMBH, Stuttgart (DE)
Filed by Robert Bosch GmbH, Stuttgart (DE)
Filed on Aug. 24, 2022, as Appl. No. 17/894,358.
Claims priority of application No. 21198202 (EP), filed on Sep. 22, 2021.
Prior Publication US 2023/0101810 A1, Mar. 30, 2023
Int. Cl. G06V 10/26 (2022.01); G06V 10/764 (2022.01); G06V 10/77 (2022.01); G06V 10/82 (2022.01)
CPC G06V 10/26 (2022.01) [G06V 10/764 (2022.01); G06V 10/7715 (2022.01); G06V 10/82 (2022.01)] 12 Claims
OG exemplary drawing
 
1. A computer-implemented method for determining an output signal characterizing a semantic segmentation and/or an instance segmentation of an image, the method comprising the following steps:
determining a first intermediate output signal from a machine learning system, the first intermediate output signal characterizing a semantic segmentation and/or an instance segmentation of the image;
adapting parameters of the machine learning system based on a loss function, wherein the loss function characterizes an entropy or a cross-entropy of the first intermediate output signal; and
determining the output signal from the machine learning system based on the image and the adapted parameters;
wherein the loss function characterizes a mean entropy of classifications obtained for pixels of the image;
wherein a second intermediate output signal is determined based on the first intermediate output signal by using a transformation function,
wherein the second intermediate output signal characterizes a semantic segmentation and/or an instance segmentation of the image and the cross-entropy is determined based on the first intermediate output signal and the second intermediate output signal; and
wherein the transformation function characterizes an edge-preserving smoothing filter.