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A Method of License Plate Location and Character Recognition based on CNN
( Wei Fang ),( Weinan Yi ),( Lin Pang ),( Shuonan Hou ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.8
At the present time, the economy continues to flourish, and private cars have become the means of choice for most people. Therefore, the license plate recognition technology has become an indispensable part of intelligent transportation, with research and application value. In recent years,the convolution neural network for image classification is an application of deep learning on image processing. This paper proposes a strategy to improve the YOLO model by studying the deep learning convolutional neural network (CNN) and related target detection methods, and combines the OpenCV and TensorFlow frameworks to achieve efficient recognition of license plate characters. The experimental results show that target detection method based on YOLO is beneficial to shorten the training process and achieve a good level of accuracy.
Distortion Correction Modeling Method for Zoom Lens Cameras with Bundle Adjustment
Wei Fang,Lianyu Zheng 한국광학회 2016 Current Optics and Photonics Vol.20 No.1
For visual measurement under dynamic scenarios, a zoom lens camera is more flexible than a fixedone. However, the challenges of distortion prediction within the whole focal range limit the widespreadapplication of zoom lens cameras greatly. Thus, a novel sequential distortion correction method for a zoomlens camera is proposed in this study. In this paper, a distortion assessment method without coupling effectis depicted by an elaborated chessboard pattern. Then, the appropriate distortion correction model for azoom lens camera is derived from the comparisons of some existing models and methods. To gain arectified image at any zoom settings, a global distortion correction modeling method is developed withbundle adjustment. Based on some selected zoom settings, the optimized quadratic functions of distortionparameters are obtained from the global perspective. Using the proposed method, we can rectify all imagesfrom the calibrated zoom lens camera. Experimental results of different zoom lens cameras validate thefeasibility and effectiveness of the proposed method.
A New Distributed Log Anomaly Detection Method based on Message Middleware and ATT-GRU
Wei Fang,Xuelei Jia,Wen Zhang,Victor S. Sheng 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.2
Logs play an important role in mastering the health of the system, experienced operation and maintenance engineer can judge which part of the system has a problem by checking the logs. In recent years, many system architectures have changed from single application to distributed application, which leads to a very huge number of logs in the system and manually check the logs to find system errors impractically. To solve the above problems, we propose a method based on Message Middleware and ATT-GRU (Attention Gate Recurrent Unit) to detect the logs anomaly of distributed systems. The works of this paper mainly include two aspects: (1) We design a high-performance distributed logs collection architecture to complete the logs collection of the distributed system. (2)We improve the existing GRU by introducing the attention mechanism to weight the key parts of the logs sequence, which can improve the training efficiency and recognition accuracy of the model to a certain extent. The results of experiments show that our method has better superiority and reliability.
Automatic 3D Model Acquisition for Unknown Objects Based on Hybrid Vision Technology
Wei Fang,Lianyu Zheng,BINGWEI HE,Qing Wang 한국정밀공학회 2017 International Journal of Precision Engineering and Vol.18 No.3
Three-dimensional (3D) model acquisition is the process of building a 3D model of an object. But due to the limited field of view of the scanner, this task is mainly performed by taking several scans with human intervention. In order to make the 3D modeling process efficient, a novel automatic 3D modeling method for unknown objects based on hybrid vision technology in a binocular structured light system (BSLS) is proposed. Firstly, the limit visual vacuums of the BSLS are established, and they will be used to predict the unknown area with an acquired 2.5D range image. With the 2D intensity image acquired synchronously, the coarse boundary size is recovered from Shape from Shading, and it leads the prediction of the unknown area to be more precise. Based on the combination of the predicted contours, the next best viewpoint is determined with more unknown areas visible. The proposed method can be used to obtain t
Curvature enhanced bearing fault diagnosis method using 2D vibration signal
Weifang Sun,Xincheng Cao 대한기계학회 2020 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.34 No.6
As a novel representation method, two dimensional (2D) segmentation is gaining ground as an effective condition monitoring method due to its high-level information descriptional ability. However, the accuracy of extracting frequency information is still limited by the finite gray-level and the extraction ability of distinguishable texture for each fault. To overcome these drawbacks, this research proposes a bearing fault diagnosis method using the converted 2D vibrational signal matrices. In this method, 1D vibration signals are converted into 2D matrices to exploit the fault signatures from the converted images. Curvature filtering (mean curvature) algorithm is applied to eliminate the overwhelming interfering contents and preserves the necessary edge information contained in the 2D matrix. In addition, the histogram of oriented gradients features is employed for the effective fault feature extraction. Finally, a one-versus-one support vector machine is utilized for the automatically fault classification. An experimental investigation was carried out for the performance evaluation of the proposed method. Comparison results indicate that the established method is capable of bearing fault detection with considerable accuracy.
Sun Weifang,Chen Binqiang,Yao Bin,Cao Xincheng,Feng Wei 대한기계학회 2017 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.31 No.2
The metal surface topology contains abundant information related to the health states of the cutting tool as well as the cutting operation. In this paper, we attempt to adopt 2D digital images of the machined metal surface, acquired via non-contact photo-imaging techniques, as the monitoring media. A Wallis filter based dodging algorithm is applied to cure the uneven contrast phenomenon caused by imperfect lighting illumination. 3D digital models were derived and retrieved from the digital image using a wavelet enhanced Shape from shading (SFS) transform. The minimization based SFS is presented to retrieve the 3D digital surface from the milled workpiece. The dual tree complex wavelet transform is adopted to enhance SFS such that the interfering noise can be suppressed. In the end, quantitative surface roughness indicators are utilized to estimate the surface roughness numerically. A milling cutting experiment of aero-material of aluminum alloy 7075 was carried out to verify the effectiveness of the proposed approach. The comparison results demonstrate that the proposed approach was capable of retrieving 3D surfaces of high precision. With the approach, the digital image emerges as a promising vehicle for machining condition monitoring of CNC machines.
EFFECTS OF BEAUTY VLOGGERS’ EWOM AND SPONSORED ADVERTISING – THE CASE OF SINA WEIBO
Claudia E. Henninger,Marta Blazquez-Cano,Weifang Ding 글로벌지식마케팅경영학회 2016 Global Marketing Conference Vol.2016 No.7
This article investigates the effects of beauty vloggers’ (video bloggers) eWOM and sponsored advertising on followers utilizing Sina Weibo, thereby exploring the concepts of eWOM, opinion leadership, and social status. This exploratory qualitative study found that vlogging differs from traditional blogging in that direct advertising that fosters ease of purchase of a product is appreciated by followers, whilst direct marketing, which in this case refers to simply describing the benefits of products and/or services, is seen as unfavorable. Moreover, this research found a relationship between the influence of vloggers, expertise of followers, the level of detail in adverts, and the level of trust. This provides valuable insights into attitudes and perceptions of followers of beauty vlogs, which can utilized as practical implications to develop targeted advertising strategies for companies seeking to promote their products and brands through third party vlogs.
Shaojie Zhang,Weifang Shuang,Qingkai Meng 제어·로봇·시스템학회 2018 International Journal of Control, Automation, and Vol.16 No.4
A neural adaptive compensation tracking control scheme considering the prescribed tracking performance bound is proposed for a flying wing aircraft with control surface faults, actuator saturation and uncertainties of aerodynamic parameters. Second-order command filters are introduced to avoid the saturation of the actuators, prescribed performance bound strategy is designed to characterize the convergence rate and maximum overshoot of the tracking error, uncertainties of aerodynamic parameters are approximated by online RBF neural networks, and control allocation law is designed to reduce the coupling of the flight dynamics. The closed-loop control law is given based on adaptive backstepping compensation control scheme, and the stability of the closed-loop system is proved by Lyapunov based design. Simulation results are given to illustrate the effectiveness of the proposed neural adaptive compensation control scheme.