This paper applies the Skopos theory to discussing the principles of Chinese-English translation of road signs,namely conforming to international conventions and English expression norms,providing information,and show...This paper applies the Skopos theory to discussing the principles of Chinese-English translation of road signs,namely conforming to international conventions and English expression norms,providing information,and showing local culture at the same time.展开更多
The infrastructure and construction of roads are crucial for the economic and social development of a region,but traffic-related challenges like accidents and congestion persist.Artificial Intelligence(AI)and Machine ...The infrastructure and construction of roads are crucial for the economic and social development of a region,but traffic-related challenges like accidents and congestion persist.Artificial Intelligence(AI)and Machine Learning(ML)have been used in road infrastructure and construction,particularly with the Internet of Things(IoT)devices.Object detection in Computer Vision also plays a key role in improving road infrastructure and addressing trafficrelated problems.This study aims to use You Only Look Once version 7(YOLOv7),Convolutional Block Attention Module(CBAM),the most optimized object-detection algorithm,to detect and identify traffic signs,and analyze effective combinations of adaptive optimizers like Adaptive Moment estimation(Adam),Root Mean Squared Propagation(RMSprop)and Stochastic Gradient Descent(SGD)with the YOLOv7.Using a portion of German traffic signs for training,the study investigates the feasibility of adopting smaller datasets while maintaining high accuracy.The model proposed in this study not only improves traffic safety by detecting traffic signs but also has the potential to contribute to the rapid development of autonomous vehicle systems.The study results showed an impressive accuracy of 99.7%when using a batch size of 8 and the Adam optimizer.This high level of accuracy demonstrates the effectiveness of the proposed model for the image classification task of traffic sign recognition.展开更多
As world automakers speed into operations in China,analysts are reminding them to proceed with caution "We have no intention of letting up on the accelerator," Kevin E. Wale, President and Managing Director ...As world automakers speed into operations in China,analysts are reminding them to proceed with caution "We have no intention of letting up on the accelerator," Kevin E. Wale, President and Managing Director of the GM China Group, said in early January, discussing the American automaker's plans for China. Similar to GM, China's top-selling foreign automaker, Ford says it is ready to shift its comprehensive expansion in the展开更多
文字识别技术在电力系统、车辆驾驶等领域应用十分广泛。随着人工智能技术的兴起和万物互联(Internet of Everything,IoE)的发展,厂商对随时随地获取复杂场景文字的需求也越来越迫切。针对文字识别环境背景复杂、视角畸变、字迹浅显和...文字识别技术在电力系统、车辆驾驶等领域应用十分广泛。随着人工智能技术的兴起和万物互联(Internet of Everything,IoE)的发展,厂商对随时随地获取复杂场景文字的需求也越来越迫切。针对文字识别环境背景复杂、视角畸变、字迹浅显和中英文字符混杂形似等诸多问题,设计出具有文字区域提取与校正、图像增强、文本检测和文本识别的光学字符识别(Optical Character Recognition,OCR)算法框架。设计了基于双注意力机制和内容感知上采样的DBNet文本检测模块增强网络的特征提取选择能力,提高内容感知能力,设计了融入中心损失CRNN+CTC的文本识别模块增大字符之间的特征间距。实验结果表明,改进的文本检测网络在ICDAR2015数据集上准确率提升了5.09%,召回率提高2.12%,F评分提高了3.46%。在中英文文本识别数据集中,改进的文本识别网络对中英文字符识别准确率提高了1.2%。展开更多
As the developing of the traffic and transport, road signs coating materials become important more and more. This paper introduces the development and current situation of the traffic marking coating and discusses its...As the developing of the traffic and transport, road signs coating materials become important more and more. This paper introduces the development and current situation of the traffic marking coating and discusses its raw material and application operation. C 5 petroleum resin made in china is used as major material in a hot melt traffic marking coating. To get the best material composition, orthogonal test is used and wear resistant, water resistant, acidity proof, alkaline proof, adhesive strength, fluid characteristic of the coating is researched.展开更多
本文以提高道路交通标志检测的准确率为目标,以解决目前YOLOv5模型在复杂场景下识别准确率较低的问题,拟采用改进的BoTNet结构来提高图像的整体感知能力,并通过对C3GBneckv2结构的优化,提高特征融合的效率。在此基础上,本文提出了一种...本文以提高道路交通标志检测的准确率为目标,以解决目前YOLOv5模型在复杂场景下识别准确率较低的问题,拟采用改进的BoTNet结构来提高图像的整体感知能力,并通过对C3GBneckv2结构的优化,提高特征融合的效率。在此基础上,本文提出了一种改进的MPDIoU损耗函数,使其更好地实现对交通标志的定位与形态的准确识别。实验表明,该方法能够较好地解决多个问题:准确率提升3.9%,召回率提升5.4%,F1得分与平均精确度(mean Average Precision,mAP)提升4.7%和4.6%。通过对各个模块的单独测试,发现每个模块都对系统的总体性能提高起到了非常重要的作用。本文为自动驾驶和智能交通系统中的交通标志自动检测技术提供了强有力的支持,并为视觉识别领域的应用开辟了新的路径。展开更多
Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada...Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada, during 2019, the National Collision Database shows that 28% of traffic fatalities and 42% of serious injuries occurred at intersections. Likewise, the U.S. National Highway Traffic Administration (NHTSA) found that about 40% of the estimated 5,811,000 accidents in the U.S. during the year studied were intersection-related crashes. In fact, a major survey by the car insurance industry found that nearly 85% of drivers could not identify the correct action to take when approaching a yellow traffic light at an intersection. One major reason for these accidents is the “yellow light dilemma,” the ambiguous situation where a driver should stop or proceed forward when unexpectedly faced with a yellow light. This situation is even further exacerbated by the tendency of aggressive drivers to inappropriately speed up on the yellow just to get through the traffic light. A survey of Canadian drivers conducted by the Traffic Injury Research Foundation found that 9% of drivers admitted to speeding up to get through a traffic light. Another reason for these accidents is the increased danger of making a left-hand turn on yellow. According to the National Highway Traffic Safety Association (NHTSA), left turns occur in approximately 22.2% of collisions—as opposed to just 1.2% for right turns. Moreover, a study by CNN found left turns are three times as likely to kill pedestrians than right turns. The reason left turns are so much more likely to cause an accident is because they take a driver against traffic and in the path of oncoming cars. Additionally, most of these left turns occur at the driver’s discretion—as opposed to the distressingly brief left-hand arrow at busy intersections. Drive Safe Now proposes a workable solution for reducing the number of accidents occurring during a yellow light at intersections. We believe this fairly simple solution will save lives, prevent injuries, reduce damage to public and private property, and decrease insurance costs.展开更多
基金This research was funded by 2022 Undergraduate Innovation and Entrepreneurship Training Program at the College Level,First-Class Curriculum Construction Program of USST“English Interpreting Ability Training”(YLKC202204)The Eleventh China Foreign Language Education Fund Project“On the blended teaching model of interpretation course with the synergistic development of interpretation ability and critical thinking ability”(ZGWYJYJJ11A071).
文摘This paper applies the Skopos theory to discussing the principles of Chinese-English translation of road signs,namely conforming to international conventions and English expression norms,providing information,and showing local culture at the same time.
文摘The infrastructure and construction of roads are crucial for the economic and social development of a region,but traffic-related challenges like accidents and congestion persist.Artificial Intelligence(AI)and Machine Learning(ML)have been used in road infrastructure and construction,particularly with the Internet of Things(IoT)devices.Object detection in Computer Vision also plays a key role in improving road infrastructure and addressing trafficrelated problems.This study aims to use You Only Look Once version 7(YOLOv7),Convolutional Block Attention Module(CBAM),the most optimized object-detection algorithm,to detect and identify traffic signs,and analyze effective combinations of adaptive optimizers like Adaptive Moment estimation(Adam),Root Mean Squared Propagation(RMSprop)and Stochastic Gradient Descent(SGD)with the YOLOv7.Using a portion of German traffic signs for training,the study investigates the feasibility of adopting smaller datasets while maintaining high accuracy.The model proposed in this study not only improves traffic safety by detecting traffic signs but also has the potential to contribute to the rapid development of autonomous vehicle systems.The study results showed an impressive accuracy of 99.7%when using a batch size of 8 and the Adam optimizer.This high level of accuracy demonstrates the effectiveness of the proposed model for the image classification task of traffic sign recognition.
文摘As world automakers speed into operations in China,analysts are reminding them to proceed with caution "We have no intention of letting up on the accelerator," Kevin E. Wale, President and Managing Director of the GM China Group, said in early January, discussing the American automaker's plans for China. Similar to GM, China's top-selling foreign automaker, Ford says it is ready to shift its comprehensive expansion in the
文摘文字识别技术在电力系统、车辆驾驶等领域应用十分广泛。随着人工智能技术的兴起和万物互联(Internet of Everything,IoE)的发展,厂商对随时随地获取复杂场景文字的需求也越来越迫切。针对文字识别环境背景复杂、视角畸变、字迹浅显和中英文字符混杂形似等诸多问题,设计出具有文字区域提取与校正、图像增强、文本检测和文本识别的光学字符识别(Optical Character Recognition,OCR)算法框架。设计了基于双注意力机制和内容感知上采样的DBNet文本检测模块增强网络的特征提取选择能力,提高内容感知能力,设计了融入中心损失CRNN+CTC的文本识别模块增大字符之间的特征间距。实验结果表明,改进的文本检测网络在ICDAR2015数据集上准确率提升了5.09%,召回率提高2.12%,F评分提高了3.46%。在中英文文本识别数据集中,改进的文本识别网络对中英文字符识别准确率提高了1.2%。
文摘As the developing of the traffic and transport, road signs coating materials become important more and more. This paper introduces the development and current situation of the traffic marking coating and discusses its raw material and application operation. C 5 petroleum resin made in china is used as major material in a hot melt traffic marking coating. To get the best material composition, orthogonal test is used and wear resistant, water resistant, acidity proof, alkaline proof, adhesive strength, fluid characteristic of the coating is researched.
文摘本文以提高道路交通标志检测的准确率为目标,以解决目前YOLOv5模型在复杂场景下识别准确率较低的问题,拟采用改进的BoTNet结构来提高图像的整体感知能力,并通过对C3GBneckv2结构的优化,提高特征融合的效率。在此基础上,本文提出了一种改进的MPDIoU损耗函数,使其更好地实现对交通标志的定位与形态的准确识别。实验表明,该方法能够较好地解决多个问题:准确率提升3.9%,召回率提升5.4%,F1得分与平均精确度(mean Average Precision,mAP)提升4.7%和4.6%。通过对各个模块的单独测试,发现每个模块都对系统的总体性能提高起到了非常重要的作用。本文为自动驾驶和智能交通系统中的交通标志自动检测技术提供了强有力的支持,并为视觉识别领域的应用开辟了新的路径。
文摘Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada, during 2019, the National Collision Database shows that 28% of traffic fatalities and 42% of serious injuries occurred at intersections. Likewise, the U.S. National Highway Traffic Administration (NHTSA) found that about 40% of the estimated 5,811,000 accidents in the U.S. during the year studied were intersection-related crashes. In fact, a major survey by the car insurance industry found that nearly 85% of drivers could not identify the correct action to take when approaching a yellow traffic light at an intersection. One major reason for these accidents is the “yellow light dilemma,” the ambiguous situation where a driver should stop or proceed forward when unexpectedly faced with a yellow light. This situation is even further exacerbated by the tendency of aggressive drivers to inappropriately speed up on the yellow just to get through the traffic light. A survey of Canadian drivers conducted by the Traffic Injury Research Foundation found that 9% of drivers admitted to speeding up to get through a traffic light. Another reason for these accidents is the increased danger of making a left-hand turn on yellow. According to the National Highway Traffic Safety Association (NHTSA), left turns occur in approximately 22.2% of collisions—as opposed to just 1.2% for right turns. Moreover, a study by CNN found left turns are three times as likely to kill pedestrians than right turns. The reason left turns are so much more likely to cause an accident is because they take a driver against traffic and in the path of oncoming cars. Additionally, most of these left turns occur at the driver’s discretion—as opposed to the distressingly brief left-hand arrow at busy intersections. Drive Safe Now proposes a workable solution for reducing the number of accidents occurring during a yellow light at intersections. We believe this fairly simple solution will save lives, prevent injuries, reduce damage to public and private property, and decrease insurance costs.
