An idea is presented about the development of a data processing and analysis system for ICF experiments, which is based on an object oriented framework. The design and preliminary implementation of the data processing...An idea is presented about the development of a data processing and analysis system for ICF experiments, which is based on an object oriented framework. The design and preliminary implementation of the data processing and analysis framework based on the ROOT system have been completed. Software for unfolding soft X-ray spectra has been developed to test the functions of this framework.展开更多
Object tracking,an important technology in the field of image processing and computer vision,is used to continuously track a specific object or person in an image.This technology may be effective in identifying the sa...Object tracking,an important technology in the field of image processing and computer vision,is used to continuously track a specific object or person in an image.This technology may be effective in identifying the same person within one image,but it has limitations in handling multiple images owing to the difficulty in identifying whether the object appearing in other images is the same.When tracking the same object using two or more images,there must be a way to determine that objects existing in different images are the same object.Therefore,this paper attempts to determine the same object present in different images using color information among the unique information of the object.Thus,this study proposes a multiple-object-tracking method using histogram stamp extraction in closed-circuit television applications.The proposed method determines the presence or absence of a target object in an image by comparing the similarity between the image containing the target object and other images.To this end,a unique color value of the target object is extracted based on its color distribution in the image using three methods:mean,mode,and interquartile range.The Top-N accuracy method is used to analyze the accuracy of each method,and the results show that the mean method had an accuracy of 93.5%(Top-2).Furthermore,the positive prediction value experimental results show that the accuracy of the mean method was 65.7%.As a result of the analysis,it is possible to detect and track the same object present in different images using the unique color of the object.Through the results,it is possible to track the same object that can minimize manpower without using personal information when detecting objects in different images.In the last response speed experiment,it was shown that when the mean was used,the color extraction of the object was possible in real time with 0.016954 s.Through this,it is possible to detect and track the same object in real time when using the proposed method.展开更多
文章介绍了在目标检测领域应用神经网络的方法,重点关注了对YOLO(You Only Look Once)目标检测算法的性能提升。首先,深入研究了数据处理与增强方法,包括数据归一化、图像旋转、镜像翻转和随机噪声添加等,以提高输入数据的质量;其次,采...文章介绍了在目标检测领域应用神经网络的方法,重点关注了对YOLO(You Only Look Once)目标检测算法的性能提升。首先,深入研究了数据处理与增强方法,包括数据归一化、图像旋转、镜像翻转和随机噪声添加等,以提高输入数据的质量;其次,采用经过处理的数据集,应用YOLO算法进行目标检测,并对所提方法进行了综合测试。实验结果显示,所提方法在精确度、召回率和F1分数方面略优于标准YOLO模型,取得了良好的效果。展开更多
给出了一个石油管理领域应用的面向对象公共数据模型 PDMM(petroleum data model for management) ,论述了元模型的建立与表达、类结构组织和实体定义、属性及约束规则等模型构筑技术 .强调了通过引入“活动”、“特性”等超类使模型具...给出了一个石油管理领域应用的面向对象公共数据模型 PDMM(petroleum data model for management) ,论述了元模型的建立与表达、类结构组织和实体定义、属性及约束规则等模型构筑技术 .强调了通过引入“活动”、“特性”等超类使模型具有强大描述能力的特色 ,给出了模型的 EXPRESS语言描述方法 .展开更多
基金This project supported by the National High-Tech Research and Development Plan (863-804-3)
文摘An idea is presented about the development of a data processing and analysis system for ICF experiments, which is based on an object oriented framework. The design and preliminary implementation of the data processing and analysis framework based on the ROOT system have been completed. Software for unfolding soft X-ray spectra has been developed to test the functions of this framework.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.2022R1F1A1068828).
文摘Object tracking,an important technology in the field of image processing and computer vision,is used to continuously track a specific object or person in an image.This technology may be effective in identifying the same person within one image,but it has limitations in handling multiple images owing to the difficulty in identifying whether the object appearing in other images is the same.When tracking the same object using two or more images,there must be a way to determine that objects existing in different images are the same object.Therefore,this paper attempts to determine the same object present in different images using color information among the unique information of the object.Thus,this study proposes a multiple-object-tracking method using histogram stamp extraction in closed-circuit television applications.The proposed method determines the presence or absence of a target object in an image by comparing the similarity between the image containing the target object and other images.To this end,a unique color value of the target object is extracted based on its color distribution in the image using three methods:mean,mode,and interquartile range.The Top-N accuracy method is used to analyze the accuracy of each method,and the results show that the mean method had an accuracy of 93.5%(Top-2).Furthermore,the positive prediction value experimental results show that the accuracy of the mean method was 65.7%.As a result of the analysis,it is possible to detect and track the same object present in different images using the unique color of the object.Through the results,it is possible to track the same object that can minimize manpower without using personal information when detecting objects in different images.In the last response speed experiment,it was shown that when the mean was used,the color extraction of the object was possible in real time with 0.016954 s.Through this,it is possible to detect and track the same object in real time when using the proposed method.
文摘文章介绍了在目标检测领域应用神经网络的方法,重点关注了对YOLO(You Only Look Once)目标检测算法的性能提升。首先,深入研究了数据处理与增强方法,包括数据归一化、图像旋转、镜像翻转和随机噪声添加等,以提高输入数据的质量;其次,采用经过处理的数据集,应用YOLO算法进行目标检测,并对所提方法进行了综合测试。实验结果显示,所提方法在精确度、召回率和F1分数方面略优于标准YOLO模型,取得了良好的效果。
文摘给出了一个石油管理领域应用的面向对象公共数据模型 PDMM(petroleum data model for management) ,论述了元模型的建立与表达、类结构组织和实体定义、属性及约束规则等模型构筑技术 .强调了通过引入“活动”、“特性”等超类使模型具有强大描述能力的特色 ,给出了模型的 EXPRESS语言描述方法 .
