In the context of the digital age, digital sculpture technology has been widely used in my country compared to traditional sculpture design and production methods. ZBrush is a digital sculpting and painting software that has influenced and transformed the digital sculpting profession with powerful features and an intuitive workflow. This paper discusses the use of ZBrush software as a tool for new sculpture art creation, and further explores the performance characteristics of digital sculpture applications that are different from traditional creation methods. The experience and methods of using digital technology are extracted and summarized, which can provide some learning and reference for the development of digital sculpture art in the future.
{"title":"Discussion on the performance characteristics of digital sculpture based on Zbrush","authors":"Yanjie Li, Hui Zhao","doi":"10.1117/12.2667533","DOIUrl":"https://doi.org/10.1117/12.2667533","url":null,"abstract":"In the context of the digital age, digital sculpture technology has been widely used in my country compared to traditional sculpture design and production methods. ZBrush is a digital sculpting and painting software that has influenced and transformed the digital sculpting profession with powerful features and an intuitive workflow. This paper discusses the use of ZBrush software as a tool for new sculpture art creation, and further explores the performance characteristics of digital sculpture applications that are different from traditional creation methods. The experience and methods of using digital technology are extracted and summarized, which can provide some learning and reference for the development of digital sculpture art in the future.","PeriodicalId":137914,"journal":{"name":"International Conference on Artificial Intelligence, Virtual Reality, and Visualization","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124354740","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 recent years, the aging process of China's society has accelerated, and the problem of old-age care has aroused widespread concern in society. The subway plays an increasingly important role in the urban public transportation system. Therefore, an intelligent sign system is designed. The three-dimensional environment of public space is displayed as a seamlessly connected plane environment by using virtual reality technology and quasi-physical elements consistent with the knowledge and experience of the elderly, in which the vision of public space is matched. The ASM model is used to quantitatively analyze the availability of the intelligent sign system from four dimensions: vision matching, utility-oriented analysis, interaction experience and visual effects, and proposes suggestions to optimize the subway sign system for the elderly, and puts forward design principles for the intelligent sign system.
{"title":"Research on the design of elderly suitability for subway station intelligent sign system under affordance theory","authors":"Min Wang, Qiu Yang","doi":"10.1117/12.2667344","DOIUrl":"https://doi.org/10.1117/12.2667344","url":null,"abstract":"In recent years, the aging process of China's society has accelerated, and the problem of old-age care has aroused widespread concern in society. The subway plays an increasingly important role in the urban public transportation system. Therefore, an intelligent sign system is designed. The three-dimensional environment of public space is displayed as a seamlessly connected plane environment by using virtual reality technology and quasi-physical elements consistent with the knowledge and experience of the elderly, in which the vision of public space is matched. The ASM model is used to quantitatively analyze the availability of the intelligent sign system from four dimensions: vision matching, utility-oriented analysis, interaction experience and visual effects, and proposes suggestions to optimize the subway sign system for the elderly, and puts forward design principles for the intelligent sign system.","PeriodicalId":137914,"journal":{"name":"International Conference on Artificial Intelligence, Virtual Reality, and Visualization","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126327050","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}
Wenhui Wang, Guangkai Ge, Longxi Han, Zhenghao Yang
In view of the poor accuracy of the traditional method to evaluate the ability of network security talents in the power industry, this paper proposes a method to evaluate the ability of network security talents in the power industry based on artificial intelligence. Through the establishment of talent ability evaluation system, it uses artificial intelligence algorithm to calculate the index weight value. According to the index corresponding weight to build the evaluation model,it determines the membership range of the index, and calculates the comprehensive score of the assessor's ability. Then, the paper compares the comprehensive score with the ability classification table and determines the ability level of the assessor to realize the evaluation of talent ability. The effectiveness of the designed evaluation method is verified by the demonstration of comparative experiments. The experimental results show that the evaluation results of the design method are consistent with the actual appraisal results in the process of evaluating the attack and defense penetration index of the network security staff. Therefore, it can be proved that the evaluation method of network security talents in power industry based on the artificial intelligence has high accuracy and objectivity, which is more realistic and helpful for the company to form a personnel management pattern with clear talent positioning and full use of talents.
{"title":"Ability evaluation method of network security talents in power industry based on artificial intelligence","authors":"Wenhui Wang, Guangkai Ge, Longxi Han, Zhenghao Yang","doi":"10.1117/12.2667643","DOIUrl":"https://doi.org/10.1117/12.2667643","url":null,"abstract":"In view of the poor accuracy of the traditional method to evaluate the ability of network security talents in the power industry, this paper proposes a method to evaluate the ability of network security talents in the power industry based on artificial intelligence. Through the establishment of talent ability evaluation system, it uses artificial intelligence algorithm to calculate the index weight value. According to the index corresponding weight to build the evaluation model,it determines the membership range of the index, and calculates the comprehensive score of the assessor's ability. Then, the paper compares the comprehensive score with the ability classification table and determines the ability level of the assessor to realize the evaluation of talent ability. The effectiveness of the designed evaluation method is verified by the demonstration of comparative experiments. The experimental results show that the evaluation results of the design method are consistent with the actual appraisal results in the process of evaluating the attack and defense penetration index of the network security staff. Therefore, it can be proved that the evaluation method of network security talents in power industry based on the artificial intelligence has high accuracy and objectivity, which is more realistic and helpful for the company to form a personnel management pattern with clear talent positioning and full use of talents.","PeriodicalId":137914,"journal":{"name":"International Conference on Artificial Intelligence, Virtual Reality, and Visualization","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125500561","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 multi-channel face liveness detection method based on multi-scale feature fusion is proposed to solve the problems of poor stability, poor generalization, and poor robustness against unknown attacks of existing face liveness detection models. Firstly, the method uses a multichannel residual network and introduces the center differential convolution and SimAM attention module in the residual block to improve the feature extraction ability and stability of the model. Secondly, the information contained in the feature map at different scales is further mined by multiscale feature fusion at the end of each channel. Finally, the network is supervised by using cross modal focal loss as an aid to binary cross entropy loss. Extensive evaluations in two publicly available datasets demonstrate the effectiveness, generalization, and robustness of the proposed method against unknown attacks.
{"title":"Multi-channel face liveness detection based on multi-scale feature fusion","authors":"Ziyi Wang, Yu-Ting Tang","doi":"10.1117/12.2667426","DOIUrl":"https://doi.org/10.1117/12.2667426","url":null,"abstract":"A multi-channel face liveness detection method based on multi-scale feature fusion is proposed to solve the problems of poor stability, poor generalization, and poor robustness against unknown attacks of existing face liveness detection models. Firstly, the method uses a multichannel residual network and introduces the center differential convolution and SimAM attention module in the residual block to improve the feature extraction ability and stability of the model. Secondly, the information contained in the feature map at different scales is further mined by multiscale feature fusion at the end of each channel. Finally, the network is supervised by using cross modal focal loss as an aid to binary cross entropy loss. Extensive evaluations in two publicly available datasets demonstrate the effectiveness, generalization, and robustness of the proposed method against unknown attacks.","PeriodicalId":137914,"journal":{"name":"International Conference on Artificial Intelligence, Virtual Reality, and Visualization","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116630463","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 convolutional neural network (CNN) in deep learning artificial intelligence (AI) has developed rapidly in recent years, delivering many achievements to other areas of economic life. Nevertheless, gaps in CNN-related research still exist in the field of object identification and detection in regard to active sonar images, as most research in this field is still dominated by classical algorithms. Therefore, this paper summarizes the YOLOV5 used, analyzes the existing network defects, and optimizes the identification and detection algorithms based on the YOLOV5 network framework. The practical detection sets a high requirement for the precision of the sonar pulse signals detected. Specifically, it requires the false alarm rate to be lower than the designed value and the errors in the detection parameters to be kept within the tolerable range. To increase the detection precision, this paper adds an attention enhancement module to the network based on the original YOLOV5, which significantly improves the detection parameter effects.
{"title":"A study on the pulse parameter detection based on the improved YOLOV5","authors":"Jinlin Liu, Qijun Liu, Yaping Yin, Haitao Li, Haixu Gou","doi":"10.1117/12.2667450","DOIUrl":"https://doi.org/10.1117/12.2667450","url":null,"abstract":"The convolutional neural network (CNN) in deep learning artificial intelligence (AI) has developed rapidly in recent years, delivering many achievements to other areas of economic life. Nevertheless, gaps in CNN-related research still exist in the field of object identification and detection in regard to active sonar images, as most research in this field is still dominated by classical algorithms. Therefore, this paper summarizes the YOLOV5 used, analyzes the existing network defects, and optimizes the identification and detection algorithms based on the YOLOV5 network framework. The practical detection sets a high requirement for the precision of the sonar pulse signals detected. Specifically, it requires the false alarm rate to be lower than the designed value and the errors in the detection parameters to be kept within the tolerable range. To increase the detection precision, this paper adds an attention enhancement module to the network based on the original YOLOV5, which significantly improves the detection parameter effects.","PeriodicalId":137914,"journal":{"name":"International Conference on Artificial Intelligence, Virtual Reality, and Visualization","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122803354","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}
Q. Wang, Chenxi Xu, Hongwei Du, Yuxuan Liu, Yang Liu, Yujia Fu, Kai Li, Haobin Shi
The development of intelligent manufacturing promotes the intellectualization of traditional navigation technology. Because actor-critic (AC) algorithm is difficult to converge in the actual application process, this paper uses the optimization algorithm of this method, which is called deep deterministic policy gradient (DDPG). Through the use of experience playback and dual network design, the learning rate can be greatly improved compared with the original algorithm. Because curiosity strategy has more advantages in alleviating sparse reward problem, this paper also takes curiosity mechanism as an internal reward exploration strategy and proposes the DDPG method based on improved curiosity mechanism to solve the problem that robots lack external reward in some complex environments and tasks cannot be completed. The simulation and real experiment results show that the proposed method is more stable when completing the navigation task and performs well in the long-distance autonomous navigation task.
{"title":"Research on target detection method based on attention mechanism and reinforcement learning","authors":"Q. Wang, Chenxi Xu, Hongwei Du, Yuxuan Liu, Yang Liu, Yujia Fu, Kai Li, Haobin Shi","doi":"10.1117/12.2668537","DOIUrl":"https://doi.org/10.1117/12.2668537","url":null,"abstract":"The development of intelligent manufacturing promotes the intellectualization of traditional navigation technology. Because actor-critic (AC) algorithm is difficult to converge in the actual application process, this paper uses the optimization algorithm of this method, which is called deep deterministic policy gradient (DDPG). Through the use of experience playback and dual network design, the learning rate can be greatly improved compared with the original algorithm. Because curiosity strategy has more advantages in alleviating sparse reward problem, this paper also takes curiosity mechanism as an internal reward exploration strategy and proposes the DDPG method based on improved curiosity mechanism to solve the problem that robots lack external reward in some complex environments and tasks cannot be completed. The simulation and real experiment results show that the proposed method is more stable when completing the navigation task and performs well in the long-distance autonomous navigation task.","PeriodicalId":137914,"journal":{"name":"International Conference on Artificial Intelligence, Virtual Reality, and Visualization","volume":"742 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122004337","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}
Traditional scene text spotters aim to detect and recognize entire words or sentences in natural scene images, however, the detection and recognition of every single character is also as important as the spotting of unifying words or sentences in one image. There are few specialized methods to spot single character in scene text spotting, and some word-based methods can not recognize a series of characters in images if they can not be spelled as a correct word. In addition, some early models can only detect or recognize texts which are horizontal and distinctive. We realize that it is necessary to improve some existing models for achieving the goal of spotting characters, therefore, we propose a novel method based on an improved YOLOv5 model to accomplish the character-level spotting. It’s worth noting that this method can spots characters not only in regular texts but also in irregular texts (curved texts and oriented texts).
{"title":"An efficient and effective text spotter for characters in natural scene images based on an improved YOLOv5 model","authors":"Quanxing Xu, Guanyi Zheng, Wanglong Ren, Xin Li, Zhuo Yang, Zhicheng Huang","doi":"10.1117/12.2667388","DOIUrl":"https://doi.org/10.1117/12.2667388","url":null,"abstract":"Traditional scene text spotters aim to detect and recognize entire words or sentences in natural scene images, however, the detection and recognition of every single character is also as important as the spotting of unifying words or sentences in one image. There are few specialized methods to spot single character in scene text spotting, and some word-based methods can not recognize a series of characters in images if they can not be spelled as a correct word. In addition, some early models can only detect or recognize texts which are horizontal and distinctive. We realize that it is necessary to improve some existing models for achieving the goal of spotting characters, therefore, we propose a novel method based on an improved YOLOv5 model to accomplish the character-level spotting. It’s worth noting that this method can spots characters not only in regular texts but also in irregular texts (curved texts and oriented texts).","PeriodicalId":137914,"journal":{"name":"International Conference on Artificial Intelligence, Virtual Reality, and Visualization","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127033555","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}
Vehicle target detection is a key research hotspot in the field of computer vision. At present, with the continuous development of deep learning and artificial intelligence, some excellent vehicle target detection algorithms such as YOLOv5, YOLOv4 and YOLOv3 have emerged. Therefore, in order to solve the problem of low accuracy of vehicle target detection, ensure the safety of vehicles on the road and achieve target detection more accurately. This paper provides a YoloV5-based method for detecting car objects and an improved algorithm that uses large-scale internal fusion techniques. Finally, the vehicle target detection accuracy of the improved YOLOv5 algorithm is effectively improved through experimental comparison and analysis. This is of great practical significance for promoting the development of target detection algorithms.
{"title":"Research on vehicle target detection method based on YOLOv5","authors":"Dingyuan Zhang, Deguo Yang","doi":"10.1117/12.2667369","DOIUrl":"https://doi.org/10.1117/12.2667369","url":null,"abstract":"Vehicle target detection is a key research hotspot in the field of computer vision. At present, with the continuous development of deep learning and artificial intelligence, some excellent vehicle target detection algorithms such as YOLOv5, YOLOv4 and YOLOv3 have emerged. Therefore, in order to solve the problem of low accuracy of vehicle target detection, ensure the safety of vehicles on the road and achieve target detection more accurately. This paper provides a YoloV5-based method for detecting car objects and an improved algorithm that uses large-scale internal fusion techniques. Finally, the vehicle target detection accuracy of the improved YOLOv5 algorithm is effectively improved through experimental comparison and analysis. This is of great practical significance for promoting the development of target detection algorithms.","PeriodicalId":137914,"journal":{"name":"International Conference on Artificial Intelligence, Virtual Reality, and Visualization","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121694080","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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