公开(公告)号：US20240153261A1

公开(公告)日：2024-05-09

申请号：US18546355

申请日：2022-02-11

Applicant: THALES CANADA INC.

Inventor： Ola AHMAD ,  Freddy LECUE

IPC: G06V10/82 ,  G06V10/44 ,  G06V10/75

CPC classification number: G06V10/82 ,  G06V10/454 ,  G06V10/76

Abstract: There is provided a method and system for training an object recognition machine learning model to perform object recognition in data acquired by ultrawide field of view (UW FOV) sensors to thereby obtain a distortion-aware object recognition model. The object recognition model comprises convolution layers each associated with a set of kernels. During training on a UW FOV labelled training dataset, deformable kernels are learned in a manifold space, mapped back to Euclidian space and used to perform convolutions to obtain output feature maps which are used to perform object recognition predictions. Model parameters of the distortion-aware object recognition model may be transferred to other architectures of object recognition models, which may be further compressed for deployment on embedded systems such as electronic devices on board autonomous vehicles.