公开(公告)号：US20250054269A1

公开(公告)日：2025-02-13

申请号：US18232107

申请日：2023-08-09

Applicant: HERE Global B.V.

Inventor： Hai YU ,  Xiaoying JIN ,  Amey AROSKAR

IPC: G06V10/44 ,  G06T3/40 ,  G06T5/20 ,  G06T7/12 ,  G06V10/771 ,  G06V20/13 ,  G06V20/17

Abstract: An approach is provided for generating feature data. The approach, for example, involves determining a set of break points associated with at least one road feature based on mask image data. The mask image data is associated with overhead image data comprising the at least one road feature. The approach further involves generating a set of cropped feature maps based on processing of a global feature map obtained from a global feature segmentation model and the set of break points. The global feature map is associated with the overhead image data. The approach further involves generating the feature data associated with the at least one road feature based on application of a local feature detection model on the generated set of cropped feature maps and the set of break points. The approach further involves storing the generated feature data in a geographic database.

公开(公告)号：US20220276618A1

公开(公告)日：2022-09-01

申请号：US17637361

申请日：2020-08-28

Applicant: HERE Global B.V.

Inventor： Amey AROSKAR ,  Sanjay Kumar BODDHU ,  Luke SMORON ,  Erika RODWELL

IPC: G05B13/02 ,  B60W60/00

Abstract: An approach is provided for providing dynamic model switching and/or model parameter switching (e.g., for object detection). The approach, for example, involves providing a plurality of machine learning models trained to detect one or more objects (e.g., vehicles, pedestrians, etc.) and/or road attributes (e.g., road hazards, road furniture, road signs, etc.). The approach also involves processing sensor data to determine at least one context (e.g., location), at least one use of the one or more road attributes, or a combination thereof. The approach further involves selecting at least one machine learning model of the plurality of machine learning models based on at least one context. The approach further involves providing the selected at least one machine learning model to detect the one or more objects and/or road attributes.