Patent ID: 11900646
Assignee: SIEMENS AKTIENGESELLSCHAFT
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 9:
10. A controller comprising:
a processor configured to run a deep neural net for localizing objects of a predetermined type in an input image,
wherein the deep neural net is a combination of parts of a discriminative deep counting model and a segmentation model, wherein the deep neural net is structured, such that by process of the respective input image, a respective corresponding map indicating locations of any objects of the predetermined type for each processed input image is generated,
wherein the discriminative deep counting model is trained to classify images according to a number of objects of the predetermined type depicted in each of the images, wherein the discriminative deep counting model is trained for at least two different classes corresponding to different numbers of objects of the predetermined type,
wherein the deep segmentation model is trained to segment images by classification of each pixel of a respective image according to what part of the respective image the respective pixel belongs to, and
wherein an upsampling module is added after a final convolutional layer of the deep neural net, wherein the upsampling module comprises an image processing algorithm based neither on machine learning nor on a neural net architecture, wherein the upsampling module is configured to take the generated map as an input and to generate, from the generated map, an upsampled map.