bluuebunny/crossref_metadata_2025_split huggingface dataset:
A fast and robust real-time surveillance video stitching method
Authors: Yang Tao , Jin Fenlin , Luo Jianxin 
Published: November 2020

Abstract
Real-time video stitching can build a wider field of view for surveillance, which faces a compromise between stitching speed and visual quality. A fast and robust real-time surveillance video stitching method is proposed to deal with the ghosting effect caused by moving objects and misalignments caused by background change or slight camera shift through automatic updating. By stitching key frames, parameters such as pix mapping table, stitching seams and blending weights are calculated, and most of subsequent frames are directly blended with CUDA acceleration based on the pre-calculated stitching parameters. Fast and effective algorithms are designed to detect the change of stitching seam and background during the whole stitching process, which determines whether to update the stitching seam or recalculate stitching parameters. Experiments show that this method can robustly and automatically solve the ghosting and misalignments to improve visual quality and achieve satisfactory real-time performance.
Research on aircraft skin damage identification method based on image analysis
Authors: Du Hailong , Cao Yuanxiang 
Published: November 2020

Abstract
In the field of civil aviation maintenance, it is necessary to identify aircraft skin damage, and then formulate a maintenance plan. The traditional detection method process is more complicated. This paper proposes an image-based skin damage recognition method. After pre-processing the samples to form a unified sample library, the eigenvalues of the samples are obtained by wavelet packet decomposition and gray-level co-occurrence matrix, and finally the c and g values in the optimal RBF kernel function are selected to construct a support vector machine training model and the test results show that with a low sample size, the constructed model is more accurate in identifying normal skins and accidental impacts, and the overall system recognition rate is 81.5%.
A Modeling and Implementation Framework of Situation Deductive Information
Authors: Ni Hao , Zhong Zhinong , Li Jun , Wang Li 
Published: November 2020

Abstract
This paper mainly studies the modeling and implementation framework of deductive information in large-scale situation scenarios. In view of the deficiencies of the current plotting systems in dynamic deduction, we achieve the dynamic modeling of situation information by applying deductive motions to military symbols. And we propose a dynamic adjustment strategy of situation layers. At the same time, through timing control, deduction control and script control, the situation deductive process can meet the actual combat needs, which is convenient for analysis and research. Finally, through practical development, it proves that our deduction method is feasible, and solve the key technology of situation information expression and realization in battlefield situation deduction.
Wide spectrum denoising (WSD) for super-resolution microscopy imaging using compressed sensing and a high-resolution camera
Authors: Cheng Tao , Chen Danni , Li Heng 
Published: November 2020

Abstract
Because of the lack of effective denoising methods, any form of denoising is seldom performed for super-resolution microscopy, resulting in poor temporal and spatial resolutions. We propose a denoising method for STORM raw images based on compressed sensing and high-resolution cameras. This method overcomes the limitation that the raw pixel size must be approximately equal to the standard deviation of the point spread function. This method can be effectively used to remove random noise such as Poisson and Gaussian noise from very low density to ultra-high density fluorescent molecular distribution scenarios. Therefore, it is a wide spectrum denoising algorithm. Using this method, it was demonstrated that the SNR of a raw image can be increased by approximately 7 dB. Using CVX reconstruction, only 20 frames of the raw image are needed, and the time resolution is 0.86 s. The spatial resolution is also greatly improved.
Photo Content Classification Using Convolutional Neural Network
Authors: Hou Yilin 
Published: November 2020

Abstract
This research is about photo content classification using the TensorFlow framework and the deep neural network algorithm in deep learning. Machine learning is a multidisciplinary major whose main research object is artificial intelligence, which enables machines to have the learning ability like human beings. As a branch of machine learning, deep learning analyses and interprets texts, images, and sounds by learning the rules and representations of sample data. A convolutional neural network is an approach of a deep neural network, which is mostly applied to analyse the photo content and has good performance in photo content classification. It is also the main point that the study focuses on. The Visual Geometry Group 16 (VGG16) model in the convolutional neural network was used to achieve the research objectives and has excellent performance. The research used data from CelebFaces and Kaggle, including photos about people, food, animals, and architecture. The photo content classification model in this study can classify these four types of images. Moreover, the analysis of the work, summary, as well as the future work were provided at the end.
An Environmental Characterization Method for Monocular Vision Obstacle of Rotor Aircraft
Authors: Li Biao , Wu Wenzhen , Yang Xiaohui , Ji Desheng , Lu Xiaoyu , Cao Yasheng , Wang Xi 
Published: November 2020

Abstract
Combining the structure of coding and anti-coding in the field of deep learning, we explore a method to represent the complex environment of four rotor aircraft. First, we use this structure to explore the process of dimensionality reduction and reconstruction of high dimensional image data. Second, combining this structure, we use the concept of transposition convolution to propose a network structure for depth distance estimation using monocular vision images. Finally, we get the direct physical feature information used to describe complex environment.
Dense Attention Convolutional Network for Image Classification
Authors: Zhang Han , Qin Kun , Zhang Ye , Li Zhili , Xu Kai 
Published: November 2020

Abstract
Convolutional neural networks (CNN) have made rapid progress for a series of visual tasks, but the bottom-up convolutional feature extraction process is not qualified to mimic the human visual perception process, which takes advantages of discriminative features. Although attention modules extract the top-down discriminative features and have been widely investigated in the past few years, current attention modules interrupt the bottom-up convolutional feature extraction process. To tackle this challenge, in this paper, we introduce dense connection structure to fuse discriminative features from attention modules and convolutional features, which we term as dense attention learning. Also, to alleviate the over-fitting problem caused by rapid feature dimension growth, we propose a channel-wise attention module to compress and refine the convolutional features. Based on these strategies, we build a dense attention convolutional neural network (DA-CNN) for visual recognition. Exhaustive experiments on four challenging datasets including CIFAR-10, CIFAR-100, SVHN and ImageNet demonstrate that our DA-CNN outperforms many state-of-the-art methods. Moreover, the effectiveness of our dense attention learning and channel-wise attention module is also validated.
Tooth-Marked Tongue Recognition Based on Mask Scoring R-CNN
Authors: Kong Xiangyong , Rui Yingdi , Dong Xin , Cai Jian , Liu Yanan 
Published: November 2020

Abstract
Tooth-marked tongue is one of the important tongue features in Traditional Chinese Medicine tongue diagnosis. It reflects the dysfunction of liver, spleen and kidney, and contains rich pathological information. However, the recognition of tooth-marked tongue is challenging. Most existing methods only focus on the classification of tooth-marked tongue, and the exact location and number of teeth marks were not involved, which had no great practical significance for the subsequent treatment based on syndrome differentiation. In this paper, we try to solve these problems by proposing a method based on Mask Scoring R-CNN framework and transfer learning which can extract, visualize the teeth marks and identify the number of teeth marks. First, the tongue image is fed into residual network of depth 101 layers (ResNet-101) to generate regions of interest (RoIs) via region proposal network (RPN) and RoI feature via RoIAlign. Next, MaskIOU is then predicted using the predicted mask and RoI characteristics as inputs. The proposed approach achieved F1 score of 0.95. According to these experimental results, the approach can robustly detect and segment teeth marks, which can provide a basis for the severity analysis of tooth-marked tongue.
Parallax-Tolerant Image Stitching for Outdoor Scenes
Authors: Li Chunbin , Liu Jiahang 
Published: November 2020

Abstract
Image stitching aims to obtain a natural panorama without ghosts. This paper proposes a panoramic image stitching method for outdoor scenes. This method gets the new homography matrix by analyzing the spatial distribution of the feature points of the outdoor scene image, and then combines with the local registration to achieve precise registration. In order to generate a more natural panorama, this paper also combines the result of registration with local similarity transformation and seam-cutting processing. Finally, the experimental results show that the proposed method obtains better performance than other methods in image stitching of outdoor scenes.
Multi-feature fatigue driving detection based on computer vision
Authors: Huang Juan , Lin Zihui 
Published: November 2020

Abstract
Fatigue driving is one of the main causes of traffic accidents. This paper proposes a fatigue detection method based on computer vision. The first is the introduction of an optimized algorithm, based on AdaBoost, to detect the face area, and then the ERT algorithm is used to achieve precise localization of the facial landmarks. Finally, a variety of fatigue features of eyes and mouth state associated with driving fatigue are extracted, and after the fusion of all these features, the fatigue driving detection is performed. The experimental results show that multi-feature detection is more accurate than single feature detection.
Automatic music transcription based on convolutional neural network, constant Q transform and MFCC
Authors: Meng Zhihang , Chen Wencheng 
Published: November 2020

Abstract
Automatic music transcription is a function that relies on the efficiency of the computer’s own calculation speed to recognize the pitch of external input audio and output it accurately. In the past methods, there are often problems such as inability to reflect music continuity or narrow identifiable frequency range. In order to avoid such problems, two methods different from the previous Mel Cepstral Coefficients and Constant Q Transform are selected to extract the features of music, and convolutional neural networks are used for training and recognition. Among them, the Mel Cepstrum coefficient is used to judge the timbre, and the constant Q transform is used to judge the pitch. After inputting the corresponding features into the neural network for training and learning, we can find that the recognition success rate has reached 95%.
A Spatio-Temporal Attention Convolution Block for Action Recognition
Authors: Wang Junjie , Wen Xueyan 
Published: November 2020

Abstract
We propose a simple and effective 3D neural network module (STAT) embedded in spatiotemporal attention for action recognition. For a given intermediate feature map, our module sequentially infers the distribution of attention along the two dimensions of space and time, and multiplies it with the current feature map in the form of residual to achieve adaptive generation of the next stage feature map. STAT is a 3D convolution general module combined with attention. It is compatible with any 3D convolution network and can easily replace the 3D convolution kernel. The additional overhead it generates is negligible, and it can be trained end-to-end together with ordinary 3DCNN. By comparing the performance of the currently popular 3D networks on the UCF101 and HMDB51 datasets, experiments show that STAT has certain improvements on most 3D networks, which proves that STAT has a certain universality.
Research on Ultra-Wideband Radar Target Recognition Method
Authors: Li Junxia , Zhang Qin , Zheng Guimei 
Published: November 2020

Abstract
UWB (Ultra wide-brand) radar, as a new system radar, has attracted more and more attention in military and civil fields such as target detection, imaging and recognition with its high range resolution, strong penetration, low interception rate and strong anti-interference. This paper focuses on the feature extraction methods based on pole distribution and scattering center combined with the characteristics and application directions of UWB radar. On this basis, combined with intelligent pattern recognition methods such as neural networks, fuzzy patterns, and information fusion, the problems that still need to be solved in the process of UWB radar target recognition are proposed.
Design and manufacture of lock-in amplifier
Authors: Xu Zhengqin , Zhao Wendong , Peng Laixian , Chen Juan 
Published: November 2020

Abstract
This design realizes the excellent performance of lock-in amplifier in detecting weak signal, which is composed of signal conditioning circuit and MCU control module. The single chip microcomputer is used to control the AD sampling of the filtered DC component after multiplication operation, and the FPGA is used to realize the phase shift control. Finally, the amplitude of the signal to be measured can be obtained by eliminating the gain generated in the whole circuit with the measured amplitude. After testing, it has the advantages of high sensitivity, high input impedance and low noise, and can realize accurate measurement.
Residual vibration control of a single-link flexible manipulator with variable stiffness and damping magnetorheological joint
Authors: Dong Xiaomin , Shi Kaiyuan , Li Wenfeng 
Published: November 2020

Abstract
Residual vibrations of large flexible manipulator can be easily excited due to large inertia and low damping, which greatly reduces the efficiency of the tasks. This paper describes an approach for the use of smart materials, specifically, magnetorheological fluid, in vibration control of a single-link flexible (SLF) manipulator. Considering that the systems with variable stiffness and damping have demonstrated excellent performance, a compact variable stiffness and damping magnetorheological joint (VSD-MRJ) was designed. A mathematical model of the SLF manipulator with a VSD-MRJ was established. Two independent fuzzy controllers were designed and applied to the stiffness and damping control of the joint. Finally, a test platform was built and the experimental results verified that the residual vibration suppression performance of the manipulator with the VSD-MRJ is better than the traditional rigid manipulator.
Study on the Development Process of Several Small Micro-software under the GJB5000A Three-level System
Authors: Yang Xiaoyu , Yuan Shengrui , Dang Xunyi 
Published: November 2020

Abstract
In order to standardize and normalize the development process of small micro-software, based on the requirements of GJB5000A three-level system, this study is based on the software engineering management technology of process improvement, so as to adapt to the actual management requirements of software.
Research on Tracking Resistance of Silicone Rubber Based on Laser-induced Breakdown Spectroscopy
Authors: Hua Ren , Heng Xu , Shanqiang Gu , Kun Chen , Chao An , Nan Liu 
Published: November 2020

Abstract
Silicone rubber composite materials are widely used in the external insulation equipment of power systems, and the tracking resistance grade is one of the indicators used for evaluating the performance of silicone rubber. It is of great significance to quickly detect the tracking resistance of insulator materials on site. The existing tracking resistance tests are all laboratory tests performed after sample preparation, and there is a lack of on-site detection methods. The laser-induced breakdown spectroscopy (LIBS) method was used to establish the linear relationship between the amount of ablation due to tracking and the background radiation intensity of the experimental LIBS spectrum, and the influence of silica and alumina trihydrate (ATH) fillers on the material’s tracking resistance was studied. This study showed that the LIBS technology can be used to detect the tracking resistance of silicone rubber materials.
On Condition Maintenance Model for Complex Electromechanical Equipments Based on Remaining Useful Life and Wiener Process
Authors: Wu Minghui , Wang Xuemin , Liu Xianzhong 
Published: November 2020

Abstract
Aiming at the problem of condition based maintenance modeling for complex electromechanical equipment, a condition based maintenance model based on residual life prediction and improved Wiener process is proposed; first of all, for the degradation process character of complex electromechanical equipment, this paper proposes a residual life prediction model based on random coefficient Wiener process; To estimate the parameters of degradation process, a prior distribution construction method based on state data is proposed; And the posterior distribution and estimation of degradation process parameters are constructed by Bayes theory, and the remaining life prediction of equipment in operation is realized. Secondly, the decision model of condition based maintenance is established by balancing the reliability and economy targets with the information of remaining life; And the immune particle swarm optimization algorithm is used to solve the model. The case study shows that the residual life prediction model proposed in this paper has higher prediction accuracy and lower prediction uncertainty, the condition based maintenance decision-making model is more practical, has higher operational reliability and economy, and the convergence accuracy of the model solving algorithm is higher.
Research on Camera Calibration Method for Visual Inspection of Excavator Working Object
Authors: Zhou Guangcun , Sun Xuan , Dong Quancheng , Cao Shukun , Li Mingchun 
Published: November 2020

Abstract
In order to realize the identification and positioning of the working object when the excavator works independently, it is necessary to calibrate the binocular camera to determine that the binocular is the internal and external parameters of the camera. This paper focuses on the calibration of binocular camera, and determines the transformation relationship among world coordinate system, camera coordinate system and image coordinate system based on binocular stereo vision ranging principle. The checkerboard images that meet the calibration requirements are selected by using the visual toolbox of MATLAB. The camera calibration process is carried out to determine the camera parameters to be determined. The calibration parameters are analyzed and compared to preliminarily verify the accuracy of the calibration parameters. Finally, the error source is analyzed in QT5.14.2 programming environment combined with OpenCV3.4.10, the calibration method meets the application requirements.
Design and implementation of graphical interface of vehicle display and control system based on SylixOS
Authors: Zhang Jianwei , Yang Xiaoyu , Dong Xueyi , Tian Xingke 
Published: November 2020

Abstract
To satisfy the design requirements of the current vehicle display and control system, and in consideration of the independent controllable requirements of the current software and hardware platforms, this paper proposed a set of nationalized solution. The Loongson 2K1000 was selected as the main control chip, and the interface design and development of vehicle display control system was completed based on the SylixOS autonomous real-time operating system. This paper elaborated on the development process of the open source graphics library Qt, and proposed solutions to the screen flicker problem encountered during the development process.
Coupling characteristics of a new automatic artillery power system
Authors: Hao Li , Runji Jian , Xintai Geng 
Published: November 2020

Abstract
A new automatic artillery adopted hydraulic system as auxiliary power to solve the problem of insufficient power after unified power. Firstly, the structure and working principle of the automatic artillery were analyzed. Secondly, in order to confirm the working torque of auxiliary power, the dynamic simulation model of the new automatic artillery was established. The accuracy of the simulation model was verified by test. The effect of output torque of auxiliary power system on the firing rate and roller bearing was researched, based on the simulation model. Finally, the working characteristics of the auxiliary power system were analyzed, and the design of the auxiliary power system was carried out.
Modeling and control of multi-airfoils system of exploration robot
Authors: Nan Zhao , Ya-ping Tian , Xiang Wu 
Published: November 2020

Abstract
Most polar exploration robots use batteries or fuel engines to provide power, which greatly limits the robot’s range of motion, and may cause pollution problems, affecting the fragile external environment of Antarctica. In view of this situation, the detection robot studied in this paper adopts three sail system driven by wind directly. Firstly, referring to the wing structure, the lift and drag forces generated by the multi wing sail system are analyzed, and the coupling relationship among the thrust, roll force and lift resistance of the robot is obtained, and the lift drag coefficient function is fitted. The system dynamics of the robot in static, linear and steering motion is analyzed respectively, and the system dynamics model of the robot in different motion states is established. Then the control system of the robot is designed and manufactured. Finally, the experiment of anti sideslip ability, anti overturning ability and starting wind speed of the probe robot prototype is carried out, and the experimental data are analyzed to prove the correctness and rationality of the theoretical analysis.
Effect of high temperature ECAP process on microstructure and mechanical properties of Ti-5553 alloy
Authors: Wang Jian , Li Zhenhua , Ma Caiyun 
Published: November 2020

Abstract
Excellent mechanical properties are the key to improve the erosion resistance of materials. Superplastic deformation process ECAP is a new heat treatment method which can refine grain size, improve the microstructure of materials and the comprehensive mechanical properties of materials. In this paper, the microstructure of Ti-5553 alloy treated by ECAP process and Ti-5553 alloy without ECAP process were observed, and the effect of high temperature ECAP process on the microstructure of Ti-5553 alloy was discussed. The effect of high temperature ECAP process on the mechanical properties of Ti-5553 alloy was studied by tensile test, and the effect of high temperature ECAP process on refining microstructure and improving mechanical properties of Ti-5553 alloy was discussed mechanism.