@Article{iasc.2020.010122,
AUTHOR = {Zhiyong Dai, Jianjun Yi, Yajun Zhang, Liang He},
TITLE = {Multi-Scale Boxes Loss for Object Detection in Smart Energy},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {26},
YEAR = {2020},
NUMBER = {5},
PAGES = {887--903},
URL = {http://www.techscience.com/iasc/v26n5/40811},
ISSN = {2326-005X},
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.},
DOI = {10.32604/iasc.2020.010122}
}