Artificial Intelligence-Driven Methods for Remote Sensing Target and Object Detection
The aim of this reprint is to provide readers with an in-depth understanding of state-of-the-art technical approaches related to remote sensing target detection and object detection. Remote sensing target detection or object detection determines the presence of a target or object of interest in a re...
Zapisane w:
| Format: | Online |
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| Język: | angielski |
| Wydane: |
MDPI - Multidisciplinary Digital Publishing Institute
2025
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| Hasła przedmiotowe: | |
| Dostęp online: | ONIX_20250812T095121_9783725832316_87 |
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| _version_ | 1869527624178466816 |
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| collection | Directory of Open Access Books |
| description | The aim of this reprint is to provide readers with an in-depth understanding of state-of-the-art technical approaches related to remote sensing target detection and object detection. Remote sensing target detection or object detection determines the presence of a target or object of interest in a remote sensing image, playing a decisive role in the fields of resource detection, environmental monitoring, national security, etc. In recent years, artificial intelligence (AI) has made great progress and been successfully applied to regression, clustering, classification and many other fields. Although AI-driven approaches can handle massive quantities of data acquired by remote sensors, they require many high-quality labeled samples to deal with remote sensing big data, leading to fragile results. That is, AI-driven approaches with strong ability for feature extraction have limited performance and are still far from practical demands. Thus, target detection or object detection in the presence of a complicated background with limited labeled samples remains a challenging mission. In this reprint, leading experts in the field share their insights, latest research results, and perspectives for the future. |
| format | Online |
| id | doab-20.500.12854ir-165138 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1651382025-08-12T08:05:15Z Artificial Intelligence-Driven Methods for Remote Sensing Target and Object Detection Dong, Yanni Yang, Xiaochen Du, Qian Remote sensing Target detection Artificial intelligence Machine learning Deep learning Object detection New datasets thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general The aim of this reprint is to provide readers with an in-depth understanding of state-of-the-art technical approaches related to remote sensing target detection and object detection. Remote sensing target detection or object detection determines the presence of a target or object of interest in a remote sensing image, playing a decisive role in the fields of resource detection, environmental monitoring, national security, etc. In recent years, artificial intelligence (AI) has made great progress and been successfully applied to regression, clustering, classification and many other fields. Although AI-driven approaches can handle massive quantities of data acquired by remote sensors, they require many high-quality labeled samples to deal with remote sensing big data, leading to fragile results. That is, AI-driven approaches with strong ability for feature extraction have limited performance and are still far from practical demands. Thus, target detection or object detection in the presence of a complicated background with limited labeled samples remains a challenging mission. In this reprint, leading experts in the field share their insights, latest research results, and perspectives for the future. 2025-08-12T08:05:13Z 2025-08-12T08:05:13Z 2025 book ONIX_20250812T095121_9783725832316_87 9783725832316 9783725832323 https://directory.doabooks.org/handle/20.500.12854/165138 eng image/jpeg Attribution 4.0 International https://mdpi.com/books https://mdpi.com/books/pdfview/book/10525 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-3232-3 10.3390/books978-3-7258-3232-3 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725832316 9783725832323 614 open access |
| spellingShingle | Remote sensing Target detection Artificial intelligence Machine learning Deep learning Object detection New datasets thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general Artificial Intelligence-Driven Methods for Remote Sensing Target and Object Detection |
| title | Artificial Intelligence-Driven Methods for Remote Sensing Target and Object Detection |
| title_full | Artificial Intelligence-Driven Methods for Remote Sensing Target and Object Detection |
| title_fullStr | Artificial Intelligence-Driven Methods for Remote Sensing Target and Object Detection |
| title_full_unstemmed | Artificial Intelligence-Driven Methods for Remote Sensing Target and Object Detection |
| title_short | Artificial Intelligence-Driven Methods for Remote Sensing Target and Object Detection |
| title_sort | artificial intelligence driven methods for remote sensing target and object detection |
| topic | Remote sensing Target detection Artificial intelligence Machine learning Deep learning Object detection New datasets thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general |
| topic_facet | Remote sensing Target detection Artificial intelligence Machine learning Deep learning Object detection New datasets thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general |
| url | ONIX_20250812T095121_9783725832316_87 |