CASIA OpenIR  > 毕业生  > 硕士学位论文
Alternative TitleAircraft Detection and Recognition from Remote-Sensing Images
Thesis Advisor潘春洪
Degree Grantor中国科学院大学
Place of Conferral中国科学院自动化研究所
Degree Discipline计算机技术
Keyword目标检测 飞机 舰船 星载处理器 卷积神经网络 Objection Detection Aircraft Ship On-board Computer Convolutional Neural Network
Abstract        随着遥感卫星成像技术的发展,遥感卫星的成像分辨率得到了大幅度的提高。大量遥感卫星的成功发射,产生了海量的遥感数据,很难依靠人工去判读。如何在遥感图像中进行目标检测和识别成为一个具有重要意义的课题。同时,随着深度学习领域相关理论与技术的不断发展,目标检测和识别的相关算法得到了飞速发展,推动了整个领域应用性能的极大提升。本文在深入分析国内外研究现状的基础上,围绕着提高目标检测的精度和效率两方面展开研究,主要工作体现在以下几个方面:
  1. 遥感图像飞机目标检测算法研究
为了提高检测精度和检测速度,提出了基于Single Shot MultiBox Detector (SSD)的遥感图像目标检测算法。为了降低存储空间,同时提出了一个改进版本的检测算法。改进版本相比于基础版本有更快的检测速度和更少的参数个数。
  1. 遥感图像飞机多类别检测与识别算法研究
  1. 星载图像处理器
Other Abstract    With the development of remote sensing satellite imaging technology, remote sensing satellite imaging resolution has been greatly improved. A large number of remote sensing satellites have been successfully launched and a huge amount of image data will be produced, which cannot be read and interpreted by human in a short time. How to carry on the object detection and recognition in remote sensing image is of great importance. At the same time, the deep learning related theory and technology has made a huge progress, and target detection and recognition algorithms got rapid development. Based on in-depth analysis on the present research, this dissertation studied the key techniques of aircraft detection. The main body of our research can be summarized into the following three pieces of work:
     1. Research on the aircraft detection from remote sensing images
     For improving the detection precision and efficiency, a remote sensing image aircraft detection method based on the Single Shot MultiBox Detector (SSD) is proposed. To reduce the memory space, an improved version is also proposed. The improved version has a higher efficiency and fewer arguments than the basic one.
     2. Research on the multi-categories aircraft detection from remote sensing images
     Based on the characteristics of remote sensing image multi-categories detection and recognition and the pros and cons of the existing algorithms, a multi category recognition algorithm based on the SSD is proposed. The method proposed has a higher mAP and efficiency than previous methods.
      3. Research on on-board computer based objection detection 
     n order to meet the requirements of remote sensing image real-time detection, a target detection system is proposed, which is based on the space borne remote sensing image processor. This method implemented the in-orbit target detection, data parsing and a series of functions. The method is based on the specific requirements of the application scenario, which has optimized the detection time on various aspects.
Document Type学位论文
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
巴君. 遥感图像飞机目标检测与识别[D]. 中国科学院自动化研究所. 中国科学院大学,2016.
Files in This Item:
File Name/Size DocType Version Access License
毕业论文-终版-巴君-20160602.(3208KB)学位论文 暂不开放CC BY-NC-SAApplication Full Text
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[巴君]'s Articles
Baidu academic
Similar articles in Baidu academic
[巴君]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[巴君]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.