Metric learning-based lightweight vehicle attribute identification method
A technology of attribute recognition and metric learning, which is applied in the field of vehicle recognition, can solve the problems of slow recognition speed, low recognition rate, and high complexity of vehicle attribute recognition network, and achieve the effect of improving recognition speed and accuracy
Active Publication Date: 2020-04-10
CHONGQING INST OF GREEN & INTELLIGENT TECH CHINESE ACADEMY OF SCI
View PDF14 Cites 5 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
[0004] In view of the above existing problems in the prior art, the present invention proposes a lightweight vehicle attribute recognition method based on metric learning, which mainly solves the high complexity of the vehicle attribute recognition network , the problem of slow recognition speed and low recognition rate
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 moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment Construction
[0027] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, in the case of no conflict, the following embodiments and features in the embodiments can be combined with each other.
[0028] It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic ideas of the present invention, and only the components related to the present invention are shown in the diagrams rather than the number, shape and shape of the compo...
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
Login to View More Abstract
The invention provides a metric learning-based lightweight vehicle attribute identification method. The method comprises the following steps that: a lightweight convolutional neural network is trainedaccording to multi-angle vehicle sample images, so that a vehicle attribute recognition model can be obtained; and a vehicle image is obtained, and is input into the vehicle attribute identificationmodel, so that vehicle attributes can be obtained, wherein the vehicle attributes comprise vehicle type, color and brand information of the vehicle. With the vehicle attribute identification method provided by the invention adopted, after the to-be-identified vehicle image is acquired, depth features are directly extracted by using the lightweight convolutional neural network; and the rapid and accurate identification of various vehicle attributes such as vehicle types, colors, brands and the like can be realized by using only one such neural network.
Description
technical field [0001] The invention relates to the field of vehicle identification, in particular to a lightweight vehicle attribute identification method based on metric learning. Background technique [0002] With the rapid development of the national economy, the increase in the number of vehicles has brought great challenges to traffic supervision. Intelligent traffic security systems are considered to be the most effective solution to alleviate traffic pressure. Vehicle attribute recognition is an important technology in the field of intelligent transportation security. Realizing attribute recognition for vehicles in massive monitoring data will help people complete intelligent analysis of monitoring data, improve the computer's understanding of target vehicles, and further promote the development of intelligent transportation. . [0003] Vehicle attributes mainly include model, color, brand, etc. The traditional process of vehicle recognition is to convert the pixel ...
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
Login to View More Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G08G1/017G06N3/04G06N3/08
CPCG08G1/0175G06N3/084G06V20/54G06V2201/08G06N3/045G06F18/214
Inventor 邓平聆杨瑶罗建江杨飞张丽君周祥东石宇罗代建程俊
Owner CHONGQING INST OF GREEN & INTELLIGENT TECH CHINESE ACADEMY OF SCI