Zhiyong Dai1,*, Jianjun Yi1, Yajun Zhang1, Liang He2
Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 887-903, 2020, DOI: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. More >
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