Research progress of deep learning-based object detection of optical remote sensing image
Object detection is the core issue in the interpretation of optical remote sensing images, and it is widely used in fields such as intelligence reconnaissance, target monitoring, and disaster rescue.Firstly, combined with the research progress of deep learning optical remote sensing image object det...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2022-05-01
|
| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022071/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841539966261264384 |
|---|---|
| author | Yurong LIAO Haining WANG Cunbao LIN Yang LI Yuqiang FANG Shuyan NI |
| author_facet | Yurong LIAO Haining WANG Cunbao LIN Yang LI Yuqiang FANG Shuyan NI |
| author_sort | Yurong LIAO |
| collection | DOAJ |
| description | Object detection is the core issue in the interpretation of optical remote sensing images, and it is widely used in fields such as intelligence reconnaissance, target monitoring, and disaster rescue.Firstly, combined with the research progress of deep learning optical remote sensing image object detection algorithms, the two types of algorithms based on candidate regions and regression analysis were reviewed.Secondly, the improvement of object detection algorithms for four types of common task-specific scenes were summarized, including rotating objects, small objects, multi-scales, and dense objects.Then, combined with commonly used remote sensing image data sets, the performance of different algorithms was compared and analyzed.Finally, the issues worthy of attention in remote sensing image object detection in the future were prospected, and ideas for follow-up related research were provided. |
| format | Article |
| id | doaj-art-4081de2c565949268905722b362b0b71 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2022-05-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-4081de2c565949268905722b362b0b712025-01-14T06:29:57ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2022-05-014319020359395828Research progress of deep learning-based object detection of optical remote sensing imageYurong LIAOHaining WANGCunbao LINYang LIYuqiang FANGShuyan NIObject detection is the core issue in the interpretation of optical remote sensing images, and it is widely used in fields such as intelligence reconnaissance, target monitoring, and disaster rescue.Firstly, combined with the research progress of deep learning optical remote sensing image object detection algorithms, the two types of algorithms based on candidate regions and regression analysis were reviewed.Secondly, the improvement of object detection algorithms for four types of common task-specific scenes were summarized, including rotating objects, small objects, multi-scales, and dense objects.Then, combined with commonly used remote sensing image data sets, the performance of different algorithms was compared and analyzed.Finally, the issues worthy of attention in remote sensing image object detection in the future were prospected, and ideas for follow-up related research were provided.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022071/optical remote sensing imageobject detectiondeep learningconvolutional neural network |
| spellingShingle | Yurong LIAO Haining WANG Cunbao LIN Yang LI Yuqiang FANG Shuyan NI Research progress of deep learning-based object detection of optical remote sensing image Tongxin xuebao optical remote sensing image object detection deep learning convolutional neural network |
| title | Research progress of deep learning-based object detection of optical remote sensing image |
| title_full | Research progress of deep learning-based object detection of optical remote sensing image |
| title_fullStr | Research progress of deep learning-based object detection of optical remote sensing image |
| title_full_unstemmed | Research progress of deep learning-based object detection of optical remote sensing image |
| title_short | Research progress of deep learning-based object detection of optical remote sensing image |
| title_sort | research progress of deep learning based object detection of optical remote sensing image |
| topic | optical remote sensing image object detection deep learning convolutional neural network |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022071/ |
| work_keys_str_mv | AT yurongliao researchprogressofdeeplearningbasedobjectdetectionofopticalremotesensingimage AT hainingwang researchprogressofdeeplearningbasedobjectdetectionofopticalremotesensingimage AT cunbaolin researchprogressofdeeplearningbasedobjectdetectionofopticalremotesensingimage AT yangli researchprogressofdeeplearningbasedobjectdetectionofopticalremotesensingimage AT yuqiangfang researchprogressofdeeplearningbasedobjectdetectionofopticalremotesensingimage AT shuyanni researchprogressofdeeplearningbasedobjectdetectionofopticalremotesensingimage |