A car search method based on deep learning

A deep learning and picture technology, applied in the field of deep learning to search for cars by pictures, can solve problems such as the decline of vehicle recognition accuracy, and achieve the effects of high speed, high model accuracy, and low memory usage.

Active Publication Date: 2021-12-03
广州广电银通金融电子科技有限公司 +2
View PDF9 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method is only applicable to the front shot of the vehicle, and when the pasted signs are changed, the accuracy of vehicle recognition will be significantly reduced

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A car search method based on deep learning
  • A car search method based on deep learning
  • A car search method based on deep learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0023] Such as figure 1 As shown, the present invention is based on the deep learning method for searching cars with pictures, mainly including the following steps:

[0024] S1. Collect pictures of actual application scenarios;

[0025] S2. Automatically label the pictures acquired by S1, that is, the pictures of the same vehicle are classified into one category, and a training set and a test set are established.

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to the technical field of computer vision, specifically a deep learning-based image search method, which integrates global appearance features and local features of vehicles, and has strong generalization and robustness. Including steps: collecting pictures of actual application scenarios; automatically labeling the acquired pictures, that is, the pictures of the same car are classified into one category, establishing a training set and a test set; designing the neural network structure; inputting the samples of the training set into the neural network Carry out training in the structure to obtain the image search model; use the image search model to calculate the feature vectors of all samples in the test set; feature comparison: use the cosine distance to calculate the similarity between the target image feature vector and the sample feature vector; The obtained similarities are sorted from largest to smallest, and the results of car search by image are obtained.

Description

technical field [0001] The invention relates to the technical field of computer vision, in particular to a method for searching cars by image based on deep learning. Background technique [0002] Searching cars with pictures is an image-based vehicle retrieval technology, which aims to search for the same vehicle in different video surveillance scenarios. Statistics show that more than 65% of crimes are related to vehicles. In car-related cases, the license plate of the suspect vehicle is usually a fake or fake plate, and the identity of the vehicle cannot be locked by identifying the license plate number. Therefore, the technology of searching for cars by image based on visual appearance features has great research significance and practical value. [0003] At present, the image search technology is mainly divided into two categories, one is based on traditional image features, and the other is based on deep features. Based on traditional image features, manually designed...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06K9/32G06N3/04G06F16/732
CPCG06F16/7335G06V20/63G06V20/625G06N3/045G06F18/213G06F18/22G06F18/214
Inventor 文莉黄宇恒金晓峰梁添才赵清利
Owner 广州广电银通金融电子科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products