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Received:December 08, 2020 Revised:January 08, 2021
Received:December 08, 2020 Revised:January 08, 2021
中文摘要: 本文根据国家电网IT设备识别的具体应用场景的特点, 通过改进Faster-RCNN实现设备的精确识别定位, 进而提高了电网数据中心管理的效率. 文章主要在注意力机制、初始锚框调整以及锚框融合等方面进行改进. 通过与常见图像算法的横向比较发现改进后的模型在收敛速度上提高了30%, 精度上提高了1%.
Abstract:In this study, according to the characteristics of specific application scenarios for the IT equipment identification of State Grid, accurate identification and positioning of the equipment is realized with improved Faster-RCNN, thereby improving the management efficiency of the grid data center. The algorithm is improved mainly in terms of the attention mechanism, the initial anchor box adjustment and the anchor box fusion. The comparison with common image algorithms shows that the improved model has the convergence speed and the accuracy increased by 30% and 1%, respectively.
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引用文本：
张晓,丁云峰.基于改进Faster-RCNN的IT设备图像定位与识别.计算机系统应用,2021,30(9):288-294
ZHANG Xiao,DING Yun-Feng.Identification and Location of IT Equipment Based on Improved Faster-RCNN.COMPUTER SYSTEMS APPLICATIONS,2021,30(9):288-294
张晓,丁云峰.基于改进Faster-RCNN的IT设备图像定位与识别.计算机系统应用,2021,30(9):288-294
ZHANG Xiao,DING Yun-Feng.Identification and Location of IT Equipment Based on Improved Faster-RCNN.COMPUTER SYSTEMS APPLICATIONS,2021,30(9):288-294
