The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
May. 20, 2025

Filed:

May. 06, 2023
Applicant:

Jiangsu University, Zhenjiang, CN;

Inventors:

Hai Wang, Zhenjiang, CN;

Guirong Zhang, Zhenjiang, CN;

Yingfeng Cai, Zhenjiang, CN;

Long Chen, Zhenjiang, CN;

Yicheng Li, Zhenjiang, CN;

Qingchao Liu, Zhenjiang, CN;

Assignee:

JIANGSU UNIVERSITY, Zhenjiang, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2022.01); G06V 10/26 (2022.01); G06V 10/32 (2022.01); G06V 10/77 (2022.01); G06V 10/776 (2022.01); G06V 10/80 (2022.01); G06V 10/82 (2022.01); G06V 20/56 (2022.01);
U.S. Cl.
CPC ...
G06V 20/588 (2022.01); G06V 10/26 (2022.01); G06V 10/32 (2022.01); G06V 10/7715 (2022.01); G06V 10/776 (2022.01); G06V 10/806 (2022.01); G06V 10/82 (2022.01);
Abstract

A multi-task joint perception network model and detection method for traffic road surface information can simultaneously detect a lane line and a drivable area. A coordinate attention mechanism is integrated into a traditional feature extraction network to ensure that a feature extraction effect is enhanced while a calculated amount is not increased. In a neck network, a dilated convolution residual module is proposed to enhance performance of prediction of details by the network, and a decoder part shares features of the drivable area into lane line detection to enhance a lane line detection effect under complex road conditions. In a training stage, there is provided a alternating optimization training method to improve integral segmentation performance of the model. The multi-task joint perception network model and detection method realizes quite high accuracy and excellent speed performance in a challenging BDD100K dataset.


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