Intelligent Recognition and Detection for Unmanned Systems
The present reprint contains the 12 articles accepted and published in a Special Issue of the MDPI journal Drones entitled “Intelligent Recognition and Detection for Unmanned Systems, 2023”; this Special Issue covers a wide range of topics connected to the theory and application of AI algorithms in...
Αποθηκεύτηκε σε:
| Μορφή: | Online |
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| Γλώσσα: | Αγγλικά |
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MDPI - Multidisciplinary Digital Publishing Institute
2025
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| Θέματα: | |
| Διαθέσιμο Online: | ONIX_20250220_9783725822232_170 |
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| _version_ | 1869517349422366720 |
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| collection | Directory of Open Access Books |
| description | The present reprint contains the 12 articles accepted and published in a Special Issue of the MDPI journal Drones entitled “Intelligent Recognition and Detection for Unmanned Systems, 2023”; this Special Issue covers a wide range of topics connected to the theory and application of AI algorithms in intelligent recognition and detection for unmanned systems. These keywords include object recognition (i.e., image recognition and speech recognition), object detection, flexible CNNs, deep learning, NLP, drone, smart robot, etc. Unmanned systems (i.e., droned, robots and other intelligent systems) play an important role in many fields, i.e., disaster relief, intelligent transportation, intelligent medical service and space exploration. Furthermore, object recognition and detection have been employed extensively in these tasks. However, due to complex application environments, artificial intelligence techniques suffer from challenges in terms of robustness and flexibility. Thus, designing efficient and stable CNNs and other AI algorithms for object recognition and detection in unmanned systems is critical. It is hoped that this reprint will provide insights for those working in the area of computer vision, artificial intelligence and unmanned systems, as well as those with the proper scientific background and willing to familiarize themselves with recent advances in unmanned systems. |
| format | Online |
| id | doab-20.500.12854ir-152806 |
| 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-1528062025-02-20T13:06:06Z Intelligent Recognition and Detection for Unmanned Systems Li, Bo Tian, Chunwei Chen, Daqing Yan, Ming Deep Learning Image Applications Unmanned Aerial Vehicle thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology thema EDItEUR::P Mathematics and Science The present reprint contains the 12 articles accepted and published in a Special Issue of the MDPI journal Drones entitled “Intelligent Recognition and Detection for Unmanned Systems, 2023”; this Special Issue covers a wide range of topics connected to the theory and application of AI algorithms in intelligent recognition and detection for unmanned systems. These keywords include object recognition (i.e., image recognition and speech recognition), object detection, flexible CNNs, deep learning, NLP, drone, smart robot, etc. Unmanned systems (i.e., droned, robots and other intelligent systems) play an important role in many fields, i.e., disaster relief, intelligent transportation, intelligent medical service and space exploration. Furthermore, object recognition and detection have been employed extensively in these tasks. However, due to complex application environments, artificial intelligence techniques suffer from challenges in terms of robustness and flexibility. Thus, designing efficient and stable CNNs and other AI algorithms for object recognition and detection in unmanned systems is critical. It is hoped that this reprint will provide insights for those working in the area of computer vision, artificial intelligence and unmanned systems, as well as those with the proper scientific background and willing to familiarize themselves with recent advances in unmanned systems. 2025-02-20T13:06:02Z 2025-02-20T13:06:02Z 2024 book ONIX_20250220_9783725822232_170 9783725822232 9783725822249 https://directory.doabooks.org/handle/20.500.12854/152806 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/9925 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-2224-9 10.3390/books978-3-7258-2224-9 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725822232 9783725822249 260 Basel open access |
| spellingShingle | Deep Learning Image Applications Unmanned Aerial Vehicle thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology thema EDItEUR::P Mathematics and Science Intelligent Recognition and Detection for Unmanned Systems |
| title | Intelligent Recognition and Detection for Unmanned Systems |
| title_full | Intelligent Recognition and Detection for Unmanned Systems |
| title_fullStr | Intelligent Recognition and Detection for Unmanned Systems |
| title_full_unstemmed | Intelligent Recognition and Detection for Unmanned Systems |
| title_short | Intelligent Recognition and Detection for Unmanned Systems |
| title_sort | intelligent recognition and detection for unmanned systems |
| topic | Deep Learning Image Applications Unmanned Aerial Vehicle thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology thema EDItEUR::P Mathematics and Science |
| topic_facet | Deep Learning Image Applications Unmanned Aerial Vehicle thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology thema EDItEUR::P Mathematics and Science |
| url | ONIX_20250220_9783725822232_170 |