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:
Oct. 17, 2023

Filed:

Jul. 07, 2021
Applicant:

Dibi (Chongqing) Intelligent Technology Research Institute Co., Ltd., Chongqing, CN;

Inventors:

Yongduan Song, Chongqing, CN;

Shilei Tan, Chongqing, CN;

Li Huang, Chongqing, CN;

Ziqiang Jiang, Chongqing, CN;

Jian Liu, Chongqing, CN;

Lihui Tan, Chongqing, CN;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 18/214 (2023.01); G06N 3/08 (2023.01); G06T 3/40 (2006.01); G06F 18/2415 (2023.01);
U.S. Cl.
CPC ...
G06F 18/2148 (2023.01); G06F 18/2415 (2023.01); G06N 3/08 (2013.01); G06T 3/4046 (2013.01);
Abstract

The present disclosure provides a method for object detection and recognition based on a neural network. The method includes: adding a detection layer following three detection layers of an existing YOLOv5 network model, to construct a new YOLOv5 network model; then, training the new YOLOv5 network model by considering an overlapping area between a predicted box and a ground truth box, a center-to-center distance between the two boxes, and an aspect ratio of the two boxes; and finally, inputting a to-be-detected image into the trained new YOLOv5 network model, outputting a predicted box of an object and probability values corresponding to a class to which the object belongs, and setting a class corresponding to a maximum probability value as a predicted class of the object in the to-be-detected image. This method can quickly and effectively detect multiple classes of objects. Especially, a detection effect for small objects is more ideal.


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