Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

High-altitude parabolic trajectory identification method based on reinforcement learning

A high-altitude parabolic and reinforcement learning technology, applied in the field of high-altitude parabolic trajectory recognition based on reinforcement learning

Active Publication Date: 2021-09-14
JINAN UNIVERSITY
View PDF16 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, there are few ideas on the market to analyze and predict high-altitude parabolic trajectories from the perspective of intelligent prediction algorithms

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
  • High-altitude parabolic trajectory identification method based on reinforcement learning
  • High-altitude parabolic trajectory identification method based on reinforcement learning
  • High-altitude parabolic trajectory identification method based on reinforcement learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0043] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.

[0044] The invention relates to a high-altitude parabolic trajectory recognition method based on reinforcement learning. The method is applied to a high-altitude parabolic trajectory recognition system based on reinforcement learning. The system mainly includes a simulation environment module, a data storage unit, an action model, an object model, a DQN error function module, an image acquisition module, a preprocessing module, an image storage module, an occlusion prediction module, a cloud server and a memory module.

[0045] Th...

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 discloses a high-altitude parabolic trajectory identification method based on reinforcement learning. The method comprises the following steps: acquiring a high-altitude parabolic trajectory image of a monitored window area through an image sensor; preprocessing the high-altitude parabolic trajectory image to obtain preprocessed image information; judging whether the image sensor is shielded or not according to the preprocessed image information; when it is judged that the image sensor is not shielded, inputting the preprocessed image information to a processor, enabling the processor to obtain a pre-training target model after reinforcement learning, and performing high-altitude parabolic object recognition on the preprocessed image information through the pre-training target model to obtain high-altitude parabolic object recognition result information; and enabling the processor to store the high-altitude object throwing identification result information into a data storage unit, a cloud server and a storage so as to train and update the pre-training target model. According to the method, the high-altitude parabolic trajectory is identified through the reinforcement learning model, and the identification accuracy is improved.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to a method for identifying high-altitude parabolic trajectories based on reinforcement learning. Background technique [0002] With the further development of economies of scale and the concentration of urban population, the human production and living environment is full of various uncertainties and risks. High-altitude parabolic is called "the pain hanging over the city". It is easy to control and stop, and it is developing rapidly. Once it reaches the completed standard, it will be difficult to be controlled and stopped immediately. Therefore, it will spread rapidly in a very short period of time, causing great damage to public safety. Especially in recent years, the number of civil and criminal cases about high-altitude parabolic behavior has been increasing, and newspapers around the world have also reported incidents of high-altitude parabolic injuries, so peo...

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 Applications(China)
IPC IPC(8): G06T7/246G06T7/277G06T5/00G06T5/50G06T3/00G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06T7/251G06T7/277G06T5/50G06N3/08G06T2207/20032G06T2207/20081G06T2207/20084G06T2207/20182G06T2207/30241G06N3/045G06F18/214G06T3/02G06T5/70
Inventor 郭洪飞马向东曾云辉陈柄赞何智慧任亚平张锐
Owner JINAN UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products