A Dual Mode Detection Method for Unexploded Ordnance Based on YOLOv5 for Low Altitude Unmanned Aerial Vehicle
Unexploded ordnance (UXO) presents a significant risk to both the natural environment and human safety. Current deep learning detection mechanisms are characterized by limited interpretability, resulting in a persistent absence of detection methods that are simultaneously efficient, secure, and prec...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10858135/ |
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