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

Method and system for intelligently recognizing aircraft wreckage based on error back propagation neural network

A neural network algorithm and error back propagation technology, applied in the field of intelligent recognition, can solve the problems of low accuracy, low intelligence, and few types of recognition.

Active Publication Date: 2015-05-13
BEIHANG UNIV
View PDF4 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] The present invention provides an aircraft wreck intelligent identification method and system based on an error backpropagation neural network, the purpose of which is to overcome the defects of conventional aircraft wreck identification systems with few identification types, low intelligence, and low accuracy

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
  • Method and system for intelligently recognizing aircraft wreckage based on error back propagation neural network
  • Method and system for intelligently recognizing aircraft wreckage based on error back propagation neural network
  • Method and system for intelligently recognizing aircraft wreckage based on error back propagation neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0092] see figure 1 —— Figures 4(a)-(d), the intelligent recognition method and system of aircraft wreckage based on error backpropagation neural network proposed by the present invention can realize accurate, fast and intelligent recognition of multiple types and parts of aircraft wreckage.

[0093] 1) The present invention is an aircraft wreckage intelligent recognition system based on error back propagation neural network,

[0094] The camera device is a YS5904H variable speed night vision dome camera produced for "Tianjin Ya'an Technology Co., Ltd." to achieve image photography in the target area;

[0095] The image acquisition device is a TPV860 high-quality 9-bit A / D processing image acquisition card, which collects and processes the images taken by the camera device;

[0096] The calculation processing device is a LBOX-GM45 Core Duo Duo Fanless industrial computer produced by "Shenzhen Lingjiang Computer Co., Ltd.", a computer platform that executes neural network algorithms or...

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 provides a system for intelligently recognizing aircraft wreckage based on error back propagation neural network. The system comprises a shooting device, an image acquiring device, a calculating processing device, an alarming device and a wireless communication device; the shooting device is used for shooting a characteristic target area and transmitting the image information obtained on real time to the image acquiring device; the image acquiring device performs format conversion for the obtained real-time image information and transmits to the calculating processing device; the calculating processing module is used for processing the image information subjected to format conversion by preprocessing, image cutting, image calculating, image recognizing and neural network learning graining; the calculating processing device sends alarming information to the alarming device after effectively recognizing the target and finishes the bidirectional wireless communication with a control device through the wireless communication device. A method for intelligently recognizing aircraft wreckage based on error back propagation neural network comprises eight steps. The system and method have a good application prospect in the technical field of intelligent recognition.

Description

Technical field [0001] The present invention proposes an aircraft wreckage intelligent recognition method and system based on error back propagation neural network. Aiming at the optical image obtained by the airborne optoelectronic pod platform, the error back propagation neural network algorithm is used for target recognition to obtain the background environment. Feature target information belongs to the field of intelligent recognition technology. Background technique [0002] Aircraft wreck recognition refers to the search and recognition of aircraft wreckage such as the wings, tail, and black box of the aircraft based on the characteristic information of the aircraft. As an important transportation platform and carrying tool, airplanes have played an increasingly important role in social life, national defense and military fields. With the rapid increase in the number of flight sorties and the continuous increase in airspace flight density, various types of aircraft lost co...

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): G06K9/00G06K9/62
CPCG06V20/13G06V10/462G06F18/214
Inventor 贾佳琪段海滨徐广帅
Owner BEIHANG UNIV
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