Road damage detection using YOLO with smartphone images
D Jeong - 2020 IEEE international conference on big data (big …, 2020 - ieeexplore.ieee.org
2020 IEEE international conference on big data (big data), 2020•ieeexplore.ieee.org
Deep learning-based technology is a good key to unlock the object detection tasks in our
real world. By using deep neural networks, we could break a problem that is dangerous and
very time-consuming but has to be done every day like detecting the road state. This paper
describes the solution using YOLO to detect the various types of road damage in the IEEE
BigData Cup Challenge 2020. Our YOLOv5x based-solution is light-weight and fast, even it
has good accuracy. We achieved an F1 score of 0.58 using our ensemble model with TTA …
real world. By using deep neural networks, we could break a problem that is dangerous and
very time-consuming but has to be done every day like detecting the road state. This paper
describes the solution using YOLO to detect the various types of road damage in the IEEE
BigData Cup Challenge 2020. Our YOLOv5x based-solution is light-weight and fast, even it
has good accuracy. We achieved an F1 score of 0.58 using our ensemble model with TTA …
Deep learning-based technology is a good key to unlock the object detection tasks in our real world. By using deep neural networks, we could break a problem that is dangerous and very time-consuming but has to be done every day like detecting the road state. This paper describes the solution using YOLO to detect the various types of road damage in the IEEE BigData Cup Challenge 2020. Our YOLOv5x based-solution is light-weight and fast, even it has good accuracy. We achieved an F1 score of 0.58 using our ensemble model with TTA, and it could be an adequate candidate for detecting real road damage in real-time.
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