This paper takes the school-enterprise cooperation between the University of Electronic Science and Technology of China(UESTC)and Baidu(China)Co.,Ltd.as an example to build the Paddle Paddle(Sichuan)AI Education Innov...This paper takes the school-enterprise cooperation between the University of Electronic Science and Technology of China(UESTC)and Baidu(China)Co.,Ltd.as an example to build the Paddle Paddle(Sichuan)AI Education Innovation Center by enjoying the best of both UESTC and Baidu(China),and cooperating with 16 universities in Sichuan Province.With the support of this center,both the school and the enterprise successfully built a school-enterprise collaborative AI innovative talent training model,which mainly serves the universities,industries,and districts.Furthermore,this training model is able to facilitate the update of the industrial intelligence and the regional economic development in southwest China,and also provide a reference for deep integration of school-enterprise collaboration and the cultivation of innovative talents in electronic information fields.展开更多
随着电商及快递行业发展,物流分拣逐渐向智能化、无人化方向发展,如何稳定高效地定位快递盒并识别快递单号文字显得尤为重要。基于此,文章提出了一种基于YOLOv8和OCR(optical character recognition)的快递盒识别算法,首先采集200张各...随着电商及快递行业发展,物流分拣逐渐向智能化、无人化方向发展,如何稳定高效地定位快递盒并识别快递单号文字显得尤为重要。基于此,文章提出了一种基于YOLOv8和OCR(optical character recognition)的快递盒识别算法,首先采集200张各种快递盒图片并标定建立数据集,为使最终识别模型适应不同光照条件,通过对色温和亮度对基础数据图片集进行扩充,然后用YOLOv8进行训练得到最优模型,并验证不同色温和亮度条件下检测精度都大于95%。此基础上采用PaddleOCR完成文字提取和分类,提取所需要的目标快递盒信息,并在中国计算机设计大赛人工智能挑战赛智慧物流专项赛比赛平台LEO智能移动抓取机器人上部署了以上算法,通过实际竞赛验证了本文算法的有效性。展开更多
基金supported by the Ministry of Education’s 2022 Second Batch of Industry-university Cooperation Collaborative Education Project"PaddlePaddle Artificial Intelligence Education Innovation Center Practice Base"(Grant No.220700001065953,220700001121532)the Ministry of Education’s Second Batch of Supply-demand Docking Employment Education Project"University of Electronic Science and Technology of China-Baidu Online Network Technology(Beijing)AI Technology Talent Training Project"(Grant No.20230103592)。
文摘This paper takes the school-enterprise cooperation between the University of Electronic Science and Technology of China(UESTC)and Baidu(China)Co.,Ltd.as an example to build the Paddle Paddle(Sichuan)AI Education Innovation Center by enjoying the best of both UESTC and Baidu(China),and cooperating with 16 universities in Sichuan Province.With the support of this center,both the school and the enterprise successfully built a school-enterprise collaborative AI innovative talent training model,which mainly serves the universities,industries,and districts.Furthermore,this training model is able to facilitate the update of the industrial intelligence and the regional economic development in southwest China,and also provide a reference for deep integration of school-enterprise collaboration and the cultivation of innovative talents in electronic information fields.
文摘随着电商及快递行业发展,物流分拣逐渐向智能化、无人化方向发展,如何稳定高效地定位快递盒并识别快递单号文字显得尤为重要。基于此,文章提出了一种基于YOLOv8和OCR(optical character recognition)的快递盒识别算法,首先采集200张各种快递盒图片并标定建立数据集,为使最终识别模型适应不同光照条件,通过对色温和亮度对基础数据图片集进行扩充,然后用YOLOv8进行训练得到最优模型,并验证不同色温和亮度条件下检测精度都大于95%。此基础上采用PaddleOCR完成文字提取和分类,提取所需要的目标快递盒信息,并在中国计算机设计大赛人工智能挑战赛智慧物流专项赛比赛平台LEO智能移动抓取机器人上部署了以上算法,通过实际竞赛验证了本文算法的有效性。
