International Conference on Artificial Intelligence, Virtual Reality, and Visualization最新文献

Research on test and evaluation scheme for vehicle-mounted satellite positioning receiver 车载卫星定位接收机测试与评估方案研究

International Conference on Artificial Intelligence, Virtual Reality, and Visualization Pub Date : 2023-03-01 DOI: 10.1117/12.2667205

Guotian Ji, Hui Rong, Tong Zhu, Fujiangshan He, Guokai Jiang

引用次数: 0

Research on Image-based wildfire intelligent detection method 基于图像的野火智能检测方法研究

International Conference on Artificial Intelligence, Virtual Reality, and Visualization Pub Date : 2023-03-01 DOI: 10.1117/12.2667234

Qiang Yang, Fan Yu, G. Zhang, Dequan Guo, Ping Wang, Guangle Yao

引用次数: 0

Microfluidic chip foreign body detection based on improved YOLOx 基于改进YOLOx的微流控芯片异物检测

International Conference on Artificial Intelligence, Virtual Reality, and Visualization Pub Date : 2023-03-01 DOI: 10.1117/12.2667312

Haodong Yan, Limin Liao, Xiaodong Liu

引用次数: 1

Near-Earth aircraft wake vortex recognition based on multiple LIDAR and transformer 基于多路激光雷达和变压器的近地飞行器尾流涡识别

International Conference on Artificial Intelligence, Virtual Reality, and Visualization Pub Date : 2023-03-01 DOI: 10.1117/12.2667212

Weijun Pan, An-ning Wang

引用次数: 0

Research on the whole process of construction quality monitoring of airport asphalt road surface based on IoT 基于物联网的机场沥青路面施工质量全过程监控研究

International Conference on Artificial Intelligence, Virtual Reality, and Visualization Pub Date : 2023-03-01 DOI: 10.1117/12.2667210

Huanjing Jiao, Xiaobo Zhu, Kaidi Liu, Lei Guo, Kaidi Liu, Q. Ye

{"title":"Research on the whole process of construction quality monitoring of airport asphalt road surface based on IoT","authors":"Huanjing Jiao, Xiaobo Zhu, Kaidi Liu, Lei Guo, Kaidi Liu, Q. Ye","doi":"10.1117/12.2667210","DOIUrl":"https://doi.org/10.1117/12.2667210","url":null,"abstract":"The traditional monitoring means of airport asphalt runway construction has problems such as irregular construction operation, unreliable process control and unscientific quality assessment. To meet the higher requirements of runway construction quality monitoring process, this paper analyzes the mechanized asphalt pavement construction process and the root causes affecting the construction quality, researches the application of Internet of Things (IoT) technology in asphalt pavement mechanized construction monitoring information system, and also develops the overall structure design of asphalt pavement monitoring system based on IoT technology, completes the development of a remote monitoring system based on the Web through serial communication, network protocol and database design. Finally, the system was analyzed in the test results of the west runway overhaul project of Capital International Airport. The results showed that the system has good hardware seismic resistance, good data integrity and real-time performance, and high reliability. The active and effective use of the airport asphalt runway construction management system can reflect the runway construction process comprehensively, while it is important to promote the traditional construction monitoring to advanced automated real-time process monitoring and management.","PeriodicalId":137914,"journal":{"name":"International Conference on Artificial Intelligence, Virtual Reality, and Visualization","volume":"29 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":"121179207","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}

引用次数: 0

Few shot text classification using adaptive cross capsule network 基于自适应交叉胶囊网络的少镜头文本分类

International Conference on Artificial Intelligence, Virtual Reality, and Visualization Pub Date : 2023-03-01 DOI: 10.1117/12.2667207

Bin Qin, Yumeng Yan, Hongyu Chen

{"title":"Few shot text classification using adaptive cross capsule network","authors":"Bin Qin, Yumeng Yan, Hongyu Chen","doi":"10.1117/12.2667207","DOIUrl":"https://doi.org/10.1117/12.2667207","url":null,"abstract":"In recent years, meta-learning has become a mainstream technique for few-shot learning, and it has been widely used and achieved good results in computer vision and image processing. Based on this powerful empirical performance, we are interested in using Meta-learning frameworks in NLP to deal with the task of few-shot learning (FSL). However, due to the sparse sample size, sample-level comparisons based on other expressions are highly susceptible to interference, leading to serious overfitting problems. To achieve classification tasks, we suggest a novel Adaptive Cross-Capsule Network (ACCN) for learning generalized representations. A dynamic routing technique is utilized with the concept of a prototype network to train the support set to generalize the generalized representations of each category. The support set and the query set can fully interact dynamically to capture the essential semantic aspects of the query set following a successful non-parametric cross-attention method. Experimental results show that ACCN proposed in this paper is well adaptive to the intention classification task under additional categories, which obtain SOTA results on FewRel Datasets, which also can perform significantly better than the original classification system on Huffpost Datasets. This provides a crucial foundation for this study.","PeriodicalId":137914,"journal":{"name":"International Conference on Artificial Intelligence, Virtual Reality, and Visualization","volume":"43 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":"130099580","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}

引用次数: 0

Development of three-dimensional dynamic teaching resources of traditional Chinese medicine 三维动态中医教学资源的开发

International Conference on Artificial Intelligence, Virtual Reality, and Visualization Pub Date : 2023-03-01 DOI: 10.1117/12.2667870

Li Wang

{"title":"Development of three-dimensional dynamic teaching resources of traditional Chinese medicine","authors":"Li Wang","doi":"10.1117/12.2667870","DOIUrl":"https://doi.org/10.1117/12.2667870","url":null,"abstract":"Identification of traditional Chinese medicine is the core content in the practice teaching of traditional Chinese medicine. It requires students to master the identification method of traditional Chinese medicine and have the ability of clinical application. In daily teaching, due to the large loss of Chinese medicinal materials, the shortage of precious medicinal materials, the lack of living medicinal materials and the long observation period at each stage of living materials, the teaching effect is not good, which affects the improvement of students' ability to identify Chinese medicinal materials. Three-dimensional teaching resources can carry out three-dimensional simulation of the growth process of medicinal plants of Traditional Chinese medicine, Chinese medicine decoction pieces and their medicinal plants, help students build knowledge and improve their identification ability of medicinal materials. This paper summarizes the advantages of three-dimensional teaching resources. The development process of 3D teaching resources of Chinese medicinal materials was elaborated in detail. The development method and implementation process of 3D modeling, 3D animation, construction of virtual scene of medicinal herbs growing environment and interactive roaming of scene are emphasized. The optimization methods of model, animation and scene are discussed.","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":"130478459","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}

引用次数: 0

Deeplab V3+ based segmentation method for PV panels with aerial orthoimages 基于Deeplab V3+的光伏板航空正射影分割方法

International Conference on Artificial Intelligence, Virtual Reality, and Visualization Pub Date : 2023-03-01 DOI: 10.1117/12.2667262

Junwen Wang, Min Liu, Wenjun Yan

引用次数: 0

Concrete dam deformation prediction method based on improved LSTM deep learning 基于改进LSTM深度学习的混凝土坝变形预测方法

International Conference on Artificial Intelligence, Virtual Reality, and Visualization Pub Date : 2023-03-01 DOI: 10.1117/12.2667216

W. Li, Yifan Tan, Li-fu Xu

引用次数: 0

Adaptive exploration network policy for effective exploration in reinforcement learning 强化学习中有效探索的自适应探索网络策略

International Conference on Artificial Intelligence, Virtual Reality, and Visualization Pub Date : 2023-03-01 DOI: 10.1117/12.2667206

Min Li, William Zhu

{"title":"Adaptive exploration network policy for effective exploration in reinforcement learning","authors":"Min Li, William Zhu","doi":"10.1117/12.2667206","DOIUrl":"https://doi.org/10.1117/12.2667206","url":null,"abstract":"How to achieve effective exploration is a key issue in the training of Reinforcement learning. The known exploration policy addresses this issue by adding noise to the policy for guiding the agent exploring. However, it has two problems that 1) the exploration scale has low adaptability to the training stability due to the added noise from a fixed distribution and 2) the policy learned after the training may be locally optimal because the exploration is insufficient. Adaptive exploration policy addresses the first problem by adjusting the noise scale according to the training stability. But the learned policy may still be locally optimal. In this paper, we propose an adaptive exploration network policy to address this problem by considering exploration direction. The motivation is that the agent should explore in the direction of increasing the sample diversity to avoid the local optimum caused by insufficient exploration. Firstly, we construct a prediction network to predict the next state after the agent makes a decision at the current state. Secondly, we propose an exploration network to generate the exploration direction. To increase the sample diversity, this network is trained by maximizing the distance between the predicted next state from prediction network and the current state. Then we adjust the exploration scale to adapt to the training stability. Finally, we propose adaptive exploration network policy based on the new noise constructed by the generated exploration direction and the adaptive exploration scale. Experiments illustrate the effectiveness of our method.","PeriodicalId":137914,"journal":{"name":"International Conference on Artificial Intelligence, Virtual Reality, and Visualization","volume":"50 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":"123621611","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}

引用次数: 0