航空数据检测系统探析

Analysis of Aviation Data Detection System

随着我国社会的快速发展,航空飞行频率也在不断增加,随之而来的必然是航空事故发生概率的提升,人们的生命财产安全将会因此遭受严重损失。为了减少航空事故的出现,航空数据检测系统的嵌入就显得非常必要。基于深度学习的航空数据检测技术,可以通过神经网络主动学习目标特征,其特点是具有较高的泛化能力和可靠度,能够大幅提高航空数据目标检测的精度和准确性,本文将基于卷积神经网络来对航空数据检测系统进行研究。

With the rapid development of China’s society,the frequency of aviation flight is also increasing,which will inevitably lead to the increase in the probability of aviation accidents,and people’s lives and property safety will suffer serious losses.In order to reduce the occurrence of aviation accidents,it is very necessary to embed aviation data detection systems.Aviation data detection technology is based on deep learning,it can actively learn target features through neural networks,and is characterized by high generalization ability and reliability,which can greatly improve the precision and accuracy of aviation data target detection.This paper will study the aviation data detection system based on convolutional neural networks.