Open Access

ARTICLE

Multi-Scale Boxes Loss for Object Detection in Smart Energy

Zhiyong Dai^1,*, Jianjun Yi¹, Yajun Zhang¹, Liang He²

1 School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai, 200237, China
2 Shanghai Aerospace Control Technology Institute, Shanghai, 201109, China

* Corresponding Author: Zhiyong Dai. Email:

Intelligent Automation & Soft Computing 2020, 26(5), 887-903. https://doi.org/10.32604/iasc.2020.010122

Abstract

The rapid development of Internet of Things (IoT) technologies has boosted smart energy networks in recent years. However, power line surveillance systems still suffer from the low accuracy and efficiency of the power line area recognition and risk objects detection. This paper proposes a new customized loss function to tackle the disequilibrium of the size of objects on multi-scale feature maps in the deep learning-based detectors. To validate the new concept and improve the efficiency, we also presented a new object detection model. Experimental results are provided to exhibit the advantage of our proposed method in both accuracy and efficiency.

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Citations