2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)最新文献_第5页

Design of Unmanned Real-Time Monitoring and Analysis System for Special Area Highway Subgrade 特殊区域公路路基无人实时监控分析系统设计

2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212768

Tianjun Yang, Hongyu Shi, Kun Yu

引用次数: 0

An Classification Model of Helicoverpa assulta and Helicoverpa armigera Combining Spatial Transformation Network and Deep Convolutional Neural Network 结合空间变换网络和深度卷积神经网络的棉铃虫和棉铃虫分类模型

2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212567

Kai Liu, Yaojing Yang, Jia Yang, Liang Zhang, Minquan Zhao, Wuping Mao

{"title":"An Classification Model of Helicoverpa assulta and Helicoverpa armigera Combining Spatial Transformation Network and Deep Convolutional Neural Network","authors":"Kai Liu, Yaojing Yang, Jia Yang, Liang Zhang, Minquan Zhao, Wuping Mao","doi":"10.1109/AINIT59027.2023.10212567","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212567","url":null,"abstract":"In order to effectively classify and identify the major pests such as Helicoverpa assulta and Helicoverpa armigera in tobacco, as well as to monitor and control them subsequently, a classification and recognition algorithm called Spatial Transformer Network combined with Deep Convolutional Neural Network (STN-DCNN) model is proposed for analyzing the images of these pests. Firstly, the images of two types of pests are preprocessed using STN to extract relevant features and obtain two different sub-images. These sub-images are then fed into a DCNN to obtain predictions for the images. Finally, the cross-entropy loss function is used to measure the difference between the prediction results and the corresponding labels. The results show that the model achieves effective classification and identification of the Helicoverpa assulta and Helicoverpa armigera with a recognition rate of 89.8%. This approach can provide valuable technical support for more accurate pest identification.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115503951","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

Improved YOLOV7 Algorithm for Transmission Line Metal Fittings Equipment Detection: Algorithm Improvement for Integrating Attention Mechanism 输电线金属配件设备检测的改进YOLOV7算法:集成注意机制的改进算法

2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212865

Junnan Li, Qiumei Wang, Siyuan Hong, Liang Fan, Xiying Chen, Chuan Ai

引用次数: 1

Spatial-Temporal Local Augmentation Graph Convolutional Networks 时空局部增强图卷积网络

2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212579

Siyu Chen, Huahu Xu, Cheng Chen, Zhe Zhu

{"title":"Spatial-Temporal Local Augmentation Graph Convolutional Networks","authors":"Siyu Chen, Huahu Xu, Cheng Chen, Zhe Zhu","doi":"10.1109/AINIT59027.2023.10212579","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212579","url":null,"abstract":"Action recognition based on skeleton models has been widely focused in the field of computer vision in recent years. Most of the previous methods only focus on the change trajectory of the same joint point in the moving process, with less consideration of the correlation between joints in the moving process, and many of the current action recognition models lack sufficient consideration of local relationships, so this paper constructs a more generalized spatial-temporal skeleton graph considering the inter-frame dependence of neighboring skeletons, and introduces a local enhancement module, using the idea of local aggregation on each node for local aggregation, combining the node's own features with the aggregated features of neighboring nodes, so as to better capture the local relationships between nodes. The model can combine global and local information to provide a more comprehensive feature representation, thus improving the performance of the model. The introduction of local relationships can also increase the flexibility and sensitivity to the details of the model. Finally, we validate the proposed Spatial-Temporal Local Augmentation Graph Convolutional Networks (ST-LAGCN) model in two skeleton datasets, NTURGB+D and Kinetics, and compare it with several state-of-the-art graph neural network models for action recognition, both of which show improved performance.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114814068","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

Design of Three-Dimensional Warehouse Intelligent Control Training System Based on Industrial Robot 基于工业机器人的三维仓库智能控制训练系统设计

2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212919

Renxuan Fu, Tao Sun, Xiaoman Cao, Yuehan Xu

引用次数: 0

Improving Power System Information Security: Analysis of the Saturnin Cipher Algorithm 提高电力系统信息安全:Saturnin密码算法分析

2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212614

Ziqing Lin, B. Hu, Xiaojuan Zhang, Yayun Zhu, Jing-yi Cao, Liang Zhang, Yuan Fang

{"title":"Improving Power System Information Security: Analysis of the Saturnin Cipher Algorithm","authors":"Ziqing Lin, B. Hu, Xiaojuan Zhang, Yayun Zhu, Jing-yi Cao, Liang Zhang, Yuan Fang","doi":"10.1109/AINIT59027.2023.10212614","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212614","url":null,"abstract":"New power systems require efficient and secure communication technologies to facilitate information exchange between various devices and systems. Among these, encryption technology is key to ensuring communication security. The lightweight block cipher algorithm, Saturnin, is similar to the AES algorithm and maintains good security even in resource-limited environments. Therefore, it can be applied to various devices in the power system, such as smart meters, sensors, controllers, etc. An impossible differential analysis was conducted on the Saturnin algorithm to identify potential security vulnerabilities, thereby enhancing the security of the power system. Firstly, based on the structural characteristics of the Saturnin algorithm, sufficient conditions for the 3.5-round impossible differential distinguisher of the Saturnin algorithm were proposed and proven. Using these sufficient conditions, 64 distinguishers can be quickly constructed and divided into four categories. Secondly, these four categories of distinguishers can be extended forward by two rounds to obtain four attack paths. These four attack paths not only have the same plaintext structure but also have a large number of common key bits. By utilizing these two characteristics, the complexity of the attack scheme can be improved. Combining early plaintext death analysis techniques, a 5.5-round impossible differential attack scheme for the Saturnin algorithm was proposed. The data, storage, and time complexity are 2176.88 chosen plaintexts, 2143.88 algorithm scale, and 2176.91 times 5.5-round encryption respectively. This is currently a visible impossible differential attack scheme against the Saturnin algorithm.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122657829","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

Common Measurement Methods and Uncertainty Analysis of Noise Figure of Receiving System 接收系统噪声系数的常用测量方法及不确定度分析

2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212512

Bowen Ning, Jingjing Wang, Wei Zhang, Chenggang Gu

引用次数: 0

A Review of Motion Planning for Urban Autonomous Driving 城市自动驾驶运动规划研究进展

2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212775

Tsz Ming Qiu

{"title":"A Review of Motion Planning for Urban Autonomous Driving","authors":"Tsz Ming Qiu","doi":"10.1109/AINIT59027.2023.10212775","DOIUrl":"https://doi.org/10.1109/AINIT59027.2023.10212775","url":null,"abstract":"The rapid development of robotics technologies has aided the growth of a variety of industries. This includes the mobile industry, which relied on drivers even until now. The rising car accident rate has grabbed huge attention for autonomous driving. However, there are a number of problems with autonomous driving that still need further investigation. Motion planning would be one of them, and previous work has already been done on the topic of motion planning as well. This review has investigated multiple motion planning algorithms, which include Dijkstra's Algorithm, Astar, Rapidly-exploring Random Tree (RRT), and Artificial Potential Field (APF), that could be used for motion planning, specifically in the area of urban driving. Through identifying the characteristics of urban roads and analyzing the benefits and drawbacks of each of the algorithms, APF would be the suggested algorithm to use in motion planning for urban driving. Although previous work already proposed algorithms that could be used for motion planning, only a few of them were researched under the circumstances of urban driving. Most of the findings drew their conclusions without consideration of the uncertainty of real driving. Therefore, only few of them could be actually applied in the real-life experiment since human drivers still exist. After compared four different algorithms and their advantages and disadvantage, further research is needed for motion planning in real-world experiments, such as urban driving, rather than simulation on computers.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131188666","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

Design and Analysis of a Five-Degree-of-Freedom Moving Platform for Deep-Sea Laser Cladding 深海激光熔覆五自由度移动平台的设计与分析

2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212795

Yi-long Zhu, Kai-ben Yu, Xu Yang, Le Zong, Yu-Gang Ren, Xiao-rui Song

引用次数: 0

Research and Design of a Universal Flash Programming Algorithm for MCU External Flash Based on IAR 基于IAR的单片机外置闪存通用编程算法的研究与设计

2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) Pub Date : 2023-06-16 DOI: 10.1109/AINIT59027.2023.10212461

Hongfei Hu, Yimei Xu, Yongheng Liu, Bin Jia

引用次数: 0