Cylindrical printing nickel mesh recycling process is cumbersome, high recycling cost and low efficiency. In order to realize the rapid and efficient recovery of cylindrical printing nickel mesh. Design and research of a laser cleaning system for cylinder printing nickel screen. The folded resonator CO2 laser is designed as the laser source, the structure model of cylinder printing nickel screen laser cleaning machine is established by SolidWorks, including frame, CO2 laser, nickel mesh loading and rotating mechanism and focusing mirror moving mechanism. Static analysis and modal analysis are carried out by using the finite element software workbench, and the overall stress nephogram, strain diagram, the first six natural frequencies and corresponding vibration modes of the cylinder printing nickel screen laser cleaning machine are obtained.
{"title":"Analysis and Design of Laser Cleaner for Cylindrical Printing Nickel Mesh","authors":"Shaobing Xue, W. Zhan, Lei Zheng, M. Huang","doi":"10.1145/3421766.3421775","DOIUrl":"https://doi.org/10.1145/3421766.3421775","url":null,"abstract":"Cylindrical printing nickel mesh recycling process is cumbersome, high recycling cost and low efficiency. In order to realize the rapid and efficient recovery of cylindrical printing nickel mesh. Design and research of a laser cleaning system for cylinder printing nickel screen. The folded resonator CO2 laser is designed as the laser source, the structure model of cylinder printing nickel screen laser cleaning machine is established by SolidWorks, including frame, CO2 laser, nickel mesh loading and rotating mechanism and focusing mirror moving mechanism. Static analysis and modal analysis are carried out by using the finite element software workbench, and the overall stress nephogram, strain diagram, the first six natural frequencies and corresponding vibration modes of the cylinder printing nickel screen laser cleaning machine are obtained.","PeriodicalId":360184,"journal":{"name":"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125900048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A network traffic classification model and optimization method based on PSO-SVM is proposed in this paper to solve the difficulties of traffic classification and its low-performance model in intrusion detection system. Based on the expansion of SVM from the two-category traffic classification structure into the five-category structure, a hybrid kernel function combining Poly and RBF is constructed by model to ensure the generalization ability and model learning; and then after conducting particle swarm optimization on the various parameters of SVM model, the search spaces tablished by nonlinear inertia weight coefficient and learning factor of asynchronous optimization are conducted with fitness evaluation to achieve the optimal solution and enhance the convergence ability of algorithm. The experimental results show that the network traffic classification model and optimization method based on PSO-SVM proposed in this paper can achieve traffic classification and improve the performance of classification model.
{"title":"Network Anomaly Traffic Classification and Optimization Based on PSO-SVM","authors":"Jianhua Huang, Jianhe Zhou, Zhe Wang, Quanliang wang, Yong Peng","doi":"10.1145/3421766.3421811","DOIUrl":"https://doi.org/10.1145/3421766.3421811","url":null,"abstract":"A network traffic classification model and optimization method based on PSO-SVM is proposed in this paper to solve the difficulties of traffic classification and its low-performance model in intrusion detection system. Based on the expansion of SVM from the two-category traffic classification structure into the five-category structure, a hybrid kernel function combining Poly and RBF is constructed by model to ensure the generalization ability and model learning; and then after conducting particle swarm optimization on the various parameters of SVM model, the search spaces tablished by nonlinear inertia weight coefficient and learning factor of asynchronous optimization are conducted with fitness evaluation to achieve the optimal solution and enhance the convergence ability of algorithm. The experimental results show that the network traffic classification model and optimization method based on PSO-SVM proposed in this paper can achieve traffic classification and improve the performance of classification model.","PeriodicalId":360184,"journal":{"name":"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129720653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The HUD (head-up display) technology was first applied to aircraft. The collected data is displayed on the windshield panel of the aircraft. The purpose is to avoid errors when the pilot looks down at the required data, resulting in some irreversible problems. as a result of. The so-called head-up display refers to the integration of the flight assistance technology of the aircraft into the car. The automobile HUD also integrates some important driving data and projects it on the front windshield, and feeds it back to the driver, reducing the frequency of looking down at the instrument, preventing the driver from distracting, and reducing the occurrence of traffic accidents. The purpose of this research is to combine HUD technology with interactive design to improve the safety of vehicle driving. This research takes as the starting point which functions should be provided by the automobile HUD, and provides a reasonable "export" between the conversion between aircraft and automobile. Perfect integration of traditional cars and modern technology, thereby reducing the occurrence of car accidents. At the same time, the user-centered design ideal is used to enable consumers to quickly accept and proficiently use the technology.
{"title":"The Value and Application of Car Head-Up Display in Interactive Design","authors":"Aijun Zhu, Caizhong Zhang","doi":"10.1145/3421766.3421796","DOIUrl":"https://doi.org/10.1145/3421766.3421796","url":null,"abstract":"The HUD (head-up display) technology was first applied to aircraft. The collected data is displayed on the windshield panel of the aircraft. The purpose is to avoid errors when the pilot looks down at the required data, resulting in some irreversible problems. as a result of. The so-called head-up display refers to the integration of the flight assistance technology of the aircraft into the car. The automobile HUD also integrates some important driving data and projects it on the front windshield, and feeds it back to the driver, reducing the frequency of looking down at the instrument, preventing the driver from distracting, and reducing the occurrence of traffic accidents. The purpose of this research is to combine HUD technology with interactive design to improve the safety of vehicle driving. This research takes as the starting point which functions should be provided by the automobile HUD, and provides a reasonable \"export\" between the conversion between aircraft and automobile. Perfect integration of traditional cars and modern technology, thereby reducing the occurrence of car accidents. At the same time, the user-centered design ideal is used to enable consumers to quickly accept and proficiently use the technology.","PeriodicalId":360184,"journal":{"name":"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130146302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fringe projection profilometry technique has attracted more and more attention in the computer vision and found wide applications in the areas of high-precision measurement. This paper presents an accurate and robust system calibration method to formulate the phase-to-height conversion. This method uses the Levenberg-Marquardt nonlinear optimization algorithm to fit the phase value of a virtual reference plane, which is parallel to the line between the optical centers of the camera and the projector. The final expression just has three coefficients. With no need to manually adjust the position of components, several experiments were conducted to evaluate the performance of proposed method and demonstrated that the novel system calibration outperforms state-of-the-art methods in terms of stability and accuracy.
{"title":"Accurate and Robust System Calibration Method for Fringe Projection Profilometry","authors":"Lingbin Bu, Hongtao Huo, Fanliang Bu","doi":"10.1145/3421766.3421794","DOIUrl":"https://doi.org/10.1145/3421766.3421794","url":null,"abstract":"Fringe projection profilometry technique has attracted more and more attention in the computer vision and found wide applications in the areas of high-precision measurement. This paper presents an accurate and robust system calibration method to formulate the phase-to-height conversion. This method uses the Levenberg-Marquardt nonlinear optimization algorithm to fit the phase value of a virtual reference plane, which is parallel to the line between the optical centers of the camera and the projector. The final expression just has three coefficients. With no need to manually adjust the position of components, several experiments were conducted to evaluate the performance of proposed method and demonstrated that the novel system calibration outperforms state-of-the-art methods in terms of stability and accuracy.","PeriodicalId":360184,"journal":{"name":"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128811529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xige Zhang, Jun Liu, Dongyan Zhao, Ting Chong, Haifeng Zhang
Central Processing Unit (CPU), as one of the core devices in electronic equipment, whether it can operate safely and reliably directly affects the safety of the entire electronic equipment. However, the electronic equipment manufacturers concern much more about the functional safety of System on Chip (SoC), for the functional safety of the CPU there is no an independent and systematic solution. During the CPU design process, structure of redundant hardware and software diagnosis technology are used to reduce the random hardware failures. By using the systematic solution, the CPU can prevents unsafe states and reduce the probability of harmful events, and easily achieve SIL2 and SIL3 safety goal.
中央处理器(CPU)作为电子设备中的核心器件之一，其能否安全可靠地运行，直接影响到整个电子设备的安全。然而，电子设备制造商对SoC (System on Chip)的功能安全更为关注，对于CPU的功能安全还没有一个独立的、系统的解决方案。在CPU设计过程中，采用了冗余硬件结构和软件诊断技术，减少了随机硬件故障。通过系统的解决方案，CPU可以防止不安全状态，降低有害事件发生的概率，轻松实现SIL2和SIL3的安全目标。
{"title":"Research of CPU Functional Safety Based on IEC 61508","authors":"Xige Zhang, Jun Liu, Dongyan Zhao, Ting Chong, Haifeng Zhang","doi":"10.1145/3421766.3421782","DOIUrl":"https://doi.org/10.1145/3421766.3421782","url":null,"abstract":"Central Processing Unit (CPU), as one of the core devices in electronic equipment, whether it can operate safely and reliably directly affects the safety of the entire electronic equipment. However, the electronic equipment manufacturers concern much more about the functional safety of System on Chip (SoC), for the functional safety of the CPU there is no an independent and systematic solution. During the CPU design process, structure of redundant hardware and software diagnosis technology are used to reduce the random hardware failures. By using the systematic solution, the CPU can prevents unsafe states and reduce the probability of harmful events, and easily achieve SIL2 and SIL3 safety goal.","PeriodicalId":360184,"journal":{"name":"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115581650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
At present, under the background that data mining technology is becoming more mature and widely used in various fields, and due to the advent of the customer-oriented era and increased competition from banks, data mining technology is being widely used in the field of banking and finance to determine the target customer group And promote bank sales. Therefore, based on the Bank Marketing data in the UCI Machine Learning Repository database, this article uses the C5.0 algorithm to classify customers on the clementine experimental platform, and proposes corresponding suggestions for bank marketing based on the classification results. This article first explores and understands the Bank Marketing data set, and describes the distribution of the customer background in the data set. The quality of the data set was further explored, and the outliers and outliers were corrected by replacing them with normal data that were closest to the outliers or extreme values. This paper further selects the optimal feature variable. First, use the Filter node to filter the unimportant variables of the classification, and further select one of the more relevant variables to reduce the redundancy of the variables. The final variables are: previous, age, duration, outcome, contact, housing, job, loan, marital, education. Secondly, this paper uses sampling nodes to perform undersampling to balance the data set. On this basis, the C5.0 algorithm is used to establish a classification model and optimize parameters, and finally obtain eight classification rules. Based on this, suggestions are provided for target group determination. Finally, this article introduces the remaining four classification algorithms: C&T, QUEST, CHAID, Neural Networks, and compares the C5.0 algorithm with the four classification algorithms based on the balanced data set. It is concluded that several algorithms have certain differences and the overall prediction accuracy is good. This article combines data mining theory with practical problems of banking business, and establishes a bank target customer classification model based on C5.0 algorithm. The obtained classification rules can effectively help banks to divide customer groups and take targeted measures to improve marketing efficiency.
{"title":"Research on Bank Marketing Behavior Based on Machine Learning","authors":"Deli Wang","doi":"10.1145/3421766.3421800","DOIUrl":"https://doi.org/10.1145/3421766.3421800","url":null,"abstract":"At present, under the background that data mining technology is becoming more mature and widely used in various fields, and due to the advent of the customer-oriented era and increased competition from banks, data mining technology is being widely used in the field of banking and finance to determine the target customer group And promote bank sales. Therefore, based on the Bank Marketing data in the UCI Machine Learning Repository database, this article uses the C5.0 algorithm to classify customers on the clementine experimental platform, and proposes corresponding suggestions for bank marketing based on the classification results. This article first explores and understands the Bank Marketing data set, and describes the distribution of the customer background in the data set. The quality of the data set was further explored, and the outliers and outliers were corrected by replacing them with normal data that were closest to the outliers or extreme values. This paper further selects the optimal feature variable. First, use the Filter node to filter the unimportant variables of the classification, and further select one of the more relevant variables to reduce the redundancy of the variables. The final variables are: previous, age, duration, outcome, contact, housing, job, loan, marital, education. Secondly, this paper uses sampling nodes to perform undersampling to balance the data set. On this basis, the C5.0 algorithm is used to establish a classification model and optimize parameters, and finally obtain eight classification rules. Based on this, suggestions are provided for target group determination. Finally, this article introduces the remaining four classification algorithms: C&T, QUEST, CHAID, Neural Networks, and compares the C5.0 algorithm with the four classification algorithms based on the balanced data set. It is concluded that several algorithms have certain differences and the overall prediction accuracy is good. This article combines data mining theory with practical problems of banking business, and establishes a bank target customer classification model based on C5.0 algorithm. The obtained classification rules can effectively help banks to divide customer groups and take targeted measures to improve marketing efficiency.","PeriodicalId":360184,"journal":{"name":"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114107766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aiming at the problems of architecture design and semantic feature verification during the construction of mobile cloud computing system, a formal semantic description model for agent-based mobile cloud computing system was proposed on the basis of typed category theory. Agent was depicted as the object node in category theory, and the interaction and dependency between agents are used as morphisms. The whole cloud service system is described as a typed category diagram. On this basis, agent interaction and cooperation, and architecture design and refinement, as well as agent migration and agent substitutability and application request satisfiability, were all analyzed and discussed. Application research shows that the formal description approach enhances the semantic description ability of the system architecture, and helps to analyze and verify the specifications of mobile cloud service system.
{"title":"Formal Description Approach for Agent-Based Mobile Computing","authors":"Cong Xu, Jinkui Hou","doi":"10.1145/3421766.3421822","DOIUrl":"https://doi.org/10.1145/3421766.3421822","url":null,"abstract":"Aiming at the problems of architecture design and semantic feature verification during the construction of mobile cloud computing system, a formal semantic description model for agent-based mobile cloud computing system was proposed on the basis of typed category theory. Agent was depicted as the object node in category theory, and the interaction and dependency between agents are used as morphisms. The whole cloud service system is described as a typed category diagram. On this basis, agent interaction and cooperation, and architecture design and refinement, as well as agent migration and agent substitutability and application request satisfiability, were all analyzed and discussed. Application research shows that the formal description approach enhances the semantic description ability of the system architecture, and helps to analyze and verify the specifications of mobile cloud service system.","PeriodicalId":360184,"journal":{"name":"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114206913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We propose a method to fast capture faces in video images, in order to make full use of the screening effect of color features, in order to find the face frame in the video image more quickly, in order to cut out the face in the picture containing the face information frame, filter out the background part, and in order to expand the facial recognition algorithm application method. The method is to use the color features of each frame of the video in the video image to screen the skin color. After screening, the image is sampled and counted. If the threshold is exceeded, it is judged whether it is a human face. When determining, the face is captured and output and the threshold is corrected according to the recognized face information; if the threshold is not exceeded, skip some frames and then prejudge the frames. Experiments on videos containing face information with more complex backgrounds prove that this method can quickly find frames containing face information, and can intercept faces from frames containing face information, saving some time, and it basically does not affect the accuracy of face capture.
{"title":"A Method for Fast Capturing Human Face in Video Image Based on Color Features","authors":"Shukun Wu, Shigang Wang","doi":"10.1145/3421766.3421803","DOIUrl":"https://doi.org/10.1145/3421766.3421803","url":null,"abstract":"We propose a method to fast capture faces in video images, in order to make full use of the screening effect of color features, in order to find the face frame in the video image more quickly, in order to cut out the face in the picture containing the face information frame, filter out the background part, and in order to expand the facial recognition algorithm application method. The method is to use the color features of each frame of the video in the video image to screen the skin color. After screening, the image is sampled and counted. If the threshold is exceeded, it is judged whether it is a human face. When determining, the face is captured and output and the threshold is corrected according to the recognized face information; if the threshold is not exceeded, skip some frames and then prejudge the frames. Experiments on videos containing face information with more complex backgrounds prove that this method can quickly find frames containing face information, and can intercept faces from frames containing face information, saving some time, and it basically does not affect the accuracy of face capture.","PeriodicalId":360184,"journal":{"name":"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126099943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abnormal power consumption not only causes great safety risks to the power system, but also hinders the intelligent development of power enterprises. This study proposed a multi-feature fusion algorithm from the perspective of unsupervised learning, constructed a feature model of electricity consumption patterns, and verified the reliability of the algorithm through experiments. The research results show that the accuracy rate of the detection result of the multi-feature fusion algorithm plus power consumption mode feature model is as high as 95%, and the AUC value of its ROC curve is the largest. When the threshold is between 0.2 and 0.3, the algorithm works best. At the same time, the cluster analysis of users' electricity consumption patterns shows a good detection effect of abnormal electricity consumption behavior. This study has reference significance for the intelligent management of power systems and provides technical ideas for the safe development of power grids.
{"title":"A Study of Intelligent Analysis of Abnormal Power Consumption Behavior Based on Daily Load Curve","authors":"Zhiyuan Long","doi":"10.1145/3421766.3421818","DOIUrl":"https://doi.org/10.1145/3421766.3421818","url":null,"abstract":"Abnormal power consumption not only causes great safety risks to the power system, but also hinders the intelligent development of power enterprises. This study proposed a multi-feature fusion algorithm from the perspective of unsupervised learning, constructed a feature model of electricity consumption patterns, and verified the reliability of the algorithm through experiments. The research results show that the accuracy rate of the detection result of the multi-feature fusion algorithm plus power consumption mode feature model is as high as 95%, and the AUC value of its ROC curve is the largest. When the threshold is between 0.2 and 0.3, the algorithm works best. At the same time, the cluster analysis of users' electricity consumption patterns shows a good detection effect of abnormal electricity consumption behavior. This study has reference significance for the intelligent management of power systems and provides technical ideas for the safe development of power grids.","PeriodicalId":360184,"journal":{"name":"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126381771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we employed three machine learning models, i.e., pure 5-layer convolutional neural network, VGG-16 model, and XGBoost algorithm model. We trained and tested these models on the Fashion-MNIST dataset. By comparing the classification accuracy and the training time, the results show that 1) the pure convolutional neural network is a very effective method for clothing images classification; 2) The complex structure of VGG 16 increases the training time, and the risk of overfitting; 3) XGBoost does not show the efficiency benefits of multi-threading on this issue.
{"title":"Comparison of Different Models for Clothing Images Classification Studies","authors":"Jiacheng Luo","doi":"10.1145/3421766.3421873","DOIUrl":"https://doi.org/10.1145/3421766.3421873","url":null,"abstract":"In this paper, we employed three machine learning models, i.e., pure 5-layer convolutional neural network, VGG-16 model, and XGBoost algorithm model. We trained and tested these models on the Fashion-MNIST dataset. By comparing the classification accuracy and the training time, the results show that 1) the pure convolutional neural network is a very effective method for clothing images classification; 2) The complex structure of VGG 16 increases the training time, and the risk of overfitting; 3) XGBoost does not show the efficiency benefits of multi-threading on this issue.","PeriodicalId":360184,"journal":{"name":"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129989817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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