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计算机系统应用:2019,28(1):94-99
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基于SSD_MobileNet模型的ROS平台目标检测
(中国电子科技集团公司第32研究所, 上海 201808)
Object Detection of ROS Platform Based on SSD_MobileNet Model
(The 32 nd Research Institute of China Electronic Technology Group Corporation, Shanghai 201808, China)
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投稿时间:2018-07-30    修订日期:2018-08-27
中文摘要: 目标检测是机器人技术领域中重要的技术环节,而作为机器人开发领域中最受欢迎的平台之一,ROS (Robot Operating System)平台实现快速准确的目标检测功能是非常必要的.目前深度学习方法是实现目标检测功能的核心技术,但当前ROS平台自带的目标检测数据包实现原理仍是基于传统的局部图像特征描述方法,目标检测鲁棒性差,泛化能力弱.本文就将针对以上问题,提出一种基于SSD_MobileNet框架,结合独立制作的图像数据集训练定制的目标检测模型,并将模型集成到ROS平台实现快速准确的目标检测功能.
Abstract:Object detection plays a key role in robotics, and as one of the most popular platforms for robot development, it is very necessary for ROS (Robot Operating System) platform to achieve fast and accurate object detection. Recently, the deep learning method is the core technology to realize the object detection function, but the object detection packets carried by the ROS platform are still based on the traditional local image feature description method, which with poor robustness and weak generalization ability. Aiming at the above problems, we propose a customized object detection model based on SSD_MobileNet framework, which combines the image dataset independently, and integrate the model to the ROS platform to achieve fast and accurate object detection function.
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童星,张激.基于SSD_MobileNet模型的ROS平台目标检测.计算机系统应用,2019,28(1):94-99
TONG Xing,ZHANG Ji.Object Detection of ROS Platform Based on SSD_MobileNet Model.COMPUTER SYSTEMS APPLICATIONS,2019,28(1):94-99

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