Improvement of High-Speed Detection Algorithm for Nonwoven Material Defects Based on Machine Vision

Defect detection is vital in the nonwoven material industry,ensuring surface quality before producing finished products.Recently,deep learning and computer vision advancements have revolutionized defect detection,making it a widely adopted approach in various industrial fields.This paper mainly studied the defect detection method for nonwoven materials based on the improved Nano Det-Plus model.Using the constructed samples of defects in nonwoven materials as the research objects,transfer learning experiments were conducted based on the Nano DetPlus object detection framework.Within this framework,the Backbone,path aggregation feature pyramid network(PAFPN)and Head network models were compared and trained through a process of freezing,with the ultimate aim of bolstering the model's feature extraction abilities and elevating detection accuracy.The half-precision quantization method was used to optimize the model after transfer learning experiments,reducing model weights and computational complexity to improve the detection speed.Performance comparisons were conducted between the improved model and the original Nano Det-Plus model,YOLO,SSD and other common industrial defect detection algorithms,validating that the improved methods based on transfer learning and semi-precision quantization enabled the model to meet the practical requirements of industrial production.

Delivery Invoice Information Classification System for Joint Courier Logistics Infrastructure

With the growth of the online market,demand for logistics and courier cargo is increasing rapidly.Accordingly,in the case of urban areas,road congestion and environmental problems due to cargo vehicles are mainly occurring.The joint courier logistics system,a plan to solve this problem,aims to establish an efficient logistics transportation system by utilizing one joint logistics delivery terminal by several logistics and delivery companies.However,several courier companies use different types of courier invoices.Such a system has a problem of information data transmission interruption.Therefore,the data processing process was systematically analyzed,a practically feasible methodology was devised,and delivery invoice information processing standards were established for this.In addition,the importance of this paper can be emphasized in terms of data processing in the logistics sector,which is expected to grow rapidly in the future.The results of this study can be used as basic data for the implementation of the logistics joint delivery terminal system in the future.And it can be used as a basis for securing the operational reliability of the joint courier logistics system.

A review of vehicle detection methods based on computer vision

With the increasing number of vehicles,there has been an unprecedented pressure on the operation and maintenance of intelligent transportation systems and transportation infrastructure.In order to achieve faster and more accurate identification of traffic vehicles,computer vision and deep learning technology play a vital role and have made significant advancements.This study summarizes the current research status,latest findings,and future development trends of traditional detection algorithms and deep learning-based detection algorithms.Among the detection algorithms based on deep learning,this study focuses on the representative convolutional neural network models.Specifically,it examines the two-stage and one-stage detection algorithms,which have been extensively utilized in the field of intelligent transportation systems.Compared to traditional detection algorithms,deep learning-based detection algorithms can achieve higher accuracy and efficiency.The single-stage detection algorithm is more efficient for real-time detection,while the two-stage detection algorithm is more accurate than the single-stage detection algorithm.In the follow-up research,it is important to consider the balance between detection efficiency and detection accuracy.Additionally,vehicle missed detection and false detection in complex scenes,such as bad weather and vehicle overlap,should be taken into account.This will ensure better application of the research findings in engineering practice.

A Climatology of Extratropical Cyclones over East Asia During 1958-2001

A climatology of extratropical cyclones （ECs） over East Asia （20~ 75~N, 60^-160~E） is analyzed by applying an improved objective detection and tracking algorithm to the 4-time daily sea level pressure fields from the European Centre for Medium-range Weather Forecasts （ECMWF） reanalysis data. A total of 12914 EC processes for the period of 1958-2001 are identified, with an EC database integrated and EC activities reanalyzed using the objective algorithm. The results reveal that there are three major cyclogenesis regions： West Siberian Plain, Mongolia （to the south of Lake Baikal）, and the coastal region of East China; whereas significant cyclolysis regions are observed in Siberia north of 60~N, Northeast China, and Okhotsk Se^Northwest Pacific. It is found that the EC lifetime is largely 1 7 days while winter ECs have the shortest lifespan. The ECs are the weakest in summer among the four seasons. Strong ECs often appear in West Siberia, Northeast China, and Okhotsk Sea-Northwest Pacific. Statistical analysis based on k-means clustering has identified 6 dominating trajectories in the area south of 55~N and east of 80~E, among which 4 tracks have important impacts on weather/climate in China. ECs occurring in spring （summer） tend to travel the longest （shortest）. They move the fastest in winter, and the slowest in summer. In winter, cyclones move fast in Northeast China, some areas of the Yangtze-Huaihe River region, and the south of Japan, with speed greater than 15 m s-1. Explosively-deepening cyclones are found to occur frequently along the east coast of China, Japan, and Northwest Pacific, but very few storms occur over the inland area. Bombs prefer to occur in winter, spring, and autumn. Their annual number and intensity in 1990 and 1992 in East Asia （EA） are smaller and weaker than their counterparts in North America.