초록

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Abstract ▼ AI-Helper

Korea has a vulnerable environment from the risk of wildfires, which causes great damage every year. To prevent this, a lot of manpower is being used, but the effect is insufficient. If wildfires are detected and extinguished early through artificial intelligence technology, damage to property and p...

Korea has a vulnerable environment from the risk of wildfires, which causes great damage every year. To prevent this, a lot of manpower is being used, but the effect is insufficient. If wildfires are detected and extinguished early through artificial intelligence technology, damage to property and people can be prevented. In this paper, we studied the object double detection method with the goal of minimizing the data collection and processing process that occurs in the process of creating an object detection model to minimize the damage of wildfires. In YOLOv5, the original image is primarily detected through a single model trained on a limited image, and the object detected in the original image is cropped through Crop. The possibility of improving the false positive object detection rate was confirmed through the object double detection method that re-detects the cropped image.