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Lightweight Bird Eye View Detection Network with Bridge Block Based on YOLOv5 | IEEE Conference Publication | IEEE Xplore

Lightweight Bird Eye View Detection Network with Bridge Block Based on YOLOv5


Abstract:

In this paper, The network with a faster detection speed than the original YOLOv5 nano model is proposed. The network defined as a bridge module reduced the number of cha...Show More

Abstract:

In this paper, The network with a faster detection speed than the original YOLOv5 nano model is proposed. The network defined as a bridge module reduced the number of channels and changed the speed quickly by applying pixel-wise operation instead of using a convolution layer. Especially, element-wise addition operation of each output feature maps is the main method. As a result, the detection speed is faster than the original detection method about 30 35%. On the other hand, mAP (mean average precision) is recorded at 50.7%, which is 1.4% lower than the original detection method. However, the original detection method showed good results in 3 classes and the proposed method showed good results in 5 classes. And the proposed method detected more objects in a detection result image. Therefore, the proposed method is a more efficient object detection network.
Date of Conference: 17-19 August 2022
Date Added to IEEE Xplore: 25 October 2022
ISBN Information:
Conference Location: Ulsan, Korea, Republic of

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