With the development of intelligent phones and speech recognition technology, there is a great demand for generating meeting minutes automatically. In this paper, we design and implement Yanji, an automated system for generating meeting minutes based on speech and speaker recognition. The Yanji system realizes the following functions: recording the audio of the conference, uploading audios to IBM cloud in real time, transcribing audios to texts and identifying various speakers with IBM Speech to Text API, and finally generating complete meeting minutes. Yanji greatly reduces the recording storage space and the labor cost of listening and writing, and improves the meeting efficiency.
随着智能手机和语音识别技术的发展，会议纪要的自动生成需求越来越大。本文设计并实现了基于语音和说话人识别的会议纪要自动生成系统“延吉”。延吉系统实现了以下功能:录制会议音频，将音频实时上传到IBM云，将音频转换为文本，并通过IBM Speech to Text API识别不同的演讲者，最终生成完整的会议纪要。延吉大大减少了录音存储空间和听写的人工成本，提高了会议效率。
{"title":"Yanji: An Automated Mobile Meeting Minutes System","authors":"Xuning Chen, Fengwei Sheng, Rongxuan He, Shiwei Chen, Hongmeng Ma, Yanfeng Wu, Jing Xu","doi":"10.1109/ISCEIC53685.2021.00095","DOIUrl":"https://doi.org/10.1109/ISCEIC53685.2021.00095","url":null,"abstract":"With the development of intelligent phones and speech recognition technology, there is a great demand for generating meeting minutes automatically. In this paper, we design and implement Yanji, an automated system for generating meeting minutes based on speech and speaker recognition. The Yanji system realizes the following functions: recording the audio of the conference, uploading audios to IBM cloud in real time, transcribing audios to texts and identifying various speakers with IBM Speech to Text API, and finally generating complete meeting minutes. Yanji greatly reduces the recording storage space and the labor cost of listening and writing, and improves the meeting efficiency.","PeriodicalId":342968,"journal":{"name":"2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128056234","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}
Semi-supervised Metric Fuzzy Clustering (SMUC) is known for taking advantage of prior information of membership to guide clustering. However, SMUC has the following problem: it is easy for SMUC to reduce the effectiveness of priori information of membership guidance because of the sensitivity of algorithm to random noise, which has a negative impact on the performance of SMUC algorithm. In order to solve the problem, we propose a Laplacian Eigenmaps based Semi-supervised Metric Fuzzy Clustering algorithm (LESMUC). Firstly, K nearest neighbors are selected in the data to construct the connected graph; secondly, the weight of the graph is calculated; finally, the objective function is minimized to get the mapping matrix, and the mapping matrix is used to map the data to a new space. This process can reduce the influence of random noise in the data set on the prior information and achieve better clustering effect. Experiments on UCI data and COVID-19 CT images show the effectiveness of the proposed clustering algorithm.
{"title":"Laplacian Eigenmaps based Semi-supervised Metric Fuzzy Clustering algorithm","authors":"Hongxi Xia, Shengbing Xu, Wei Cai, Peixuan Chen, Yuanhao Zhu","doi":"10.1109/ISCEIC53685.2021.00012","DOIUrl":"https://doi.org/10.1109/ISCEIC53685.2021.00012","url":null,"abstract":"Semi-supervised Metric Fuzzy Clustering (SMUC) is known for taking advantage of prior information of membership to guide clustering. However, SMUC has the following problem: it is easy for SMUC to reduce the effectiveness of priori information of membership guidance because of the sensitivity of algorithm to random noise, which has a negative impact on the performance of SMUC algorithm. In order to solve the problem, we propose a Laplacian Eigenmaps based Semi-supervised Metric Fuzzy Clustering algorithm (LESMUC). Firstly, K nearest neighbors are selected in the data to construct the connected graph; secondly, the weight of the graph is calculated; finally, the objective function is minimized to get the mapping matrix, and the mapping matrix is used to map the data to a new space. This process can reduce the influence of random noise in the data set on the prior information and achieve better clustering effect. Experiments on UCI data and COVID-19 CT images show the effectiveness of the proposed clustering algorithm.","PeriodicalId":342968,"journal":{"name":"2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117199886","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}
General Secretary Xi Jinping’s statements on "craftsman spirit" is the concentrated embodiment of the cultural confidence of socialism with Chinese characteristics. Therefore, it is necessary to sort out the research focuses and trends of General Secretary Xi Jinping’s important statements on it and study the practical path. With the knowledge map of CiteSpace, this paper combs the literature on the elaboration of the craftsman spirit by General Secretary Xi Jinping in the past five years from 2017 to 2021. The research focuses on four dimensions: analyze the evolution of craftsman spirit from historical dimension; discuss the connotation and significance from the dimension of General Secretary Xi’s statement; explore the effective integration of craftsman spirit from the dimension of ideological and political education; think the craftsman spirit from the dimension of design education. This paper has summarized the research trend of General Secretary Xi Jinping’s statement on craftsman spirit’s integration in the future education and craftsman culture inheritance.
{"title":"Research Focus and Trend of Xi Jinping’s Statements on Craftsman Spirit : A Citespace Visualized Analysis Based on the Literature from 2017 to 2021","authors":"Dongjie Wu, Yunbing Han, Zhenwei Zhang, Haiyu Tang","doi":"10.1109/ISCEIC53685.2021.00054","DOIUrl":"https://doi.org/10.1109/ISCEIC53685.2021.00054","url":null,"abstract":"General Secretary Xi Jinping’s statements on \"craftsman spirit\" is the concentrated embodiment of the cultural confidence of socialism with Chinese characteristics. Therefore, it is necessary to sort out the research focuses and trends of General Secretary Xi Jinping’s important statements on it and study the practical path. With the knowledge map of CiteSpace, this paper combs the literature on the elaboration of the craftsman spirit by General Secretary Xi Jinping in the past five years from 2017 to 2021. The research focuses on four dimensions: analyze the evolution of craftsman spirit from historical dimension; discuss the connotation and significance from the dimension of General Secretary Xi’s statement; explore the effective integration of craftsman spirit from the dimension of ideological and political education; think the craftsman spirit from the dimension of design education. This paper has summarized the research trend of General Secretary Xi Jinping’s statement on craftsman spirit’s integration in the future education and craftsman culture inheritance.","PeriodicalId":342968,"journal":{"name":"2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC)","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115175525","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}
Pub Date : 2021-08-01DOI: 10.1109/ISCEIC53685.2021.00031
Liu Yang, Miao Li, Xinpu Deng
The image under the starry sky background lacks texture detail information. It is difficult to use visual features such as regional features, shape to achieve image registration, and the star map structure may be unknown. To address these issues, this paper proposes a fast matching algorithm for sparse star points based on the Delaunay subdivision, which uses the geometric topological structure between the star points to solve the image transformation parameters and achieve accurate registration. Experimental results show that this method can still perform correct registration even in the presence of noise, target points, rotation, and translation, or lack of star points in the star map. The average registration error of 50 sets of simulated star maps is 0.4791 pixels, and the average registration time is 3.5386 s, which can meet the requirements of registration accuracy and speed, realizes the combination of mathematical methods and graphics.
{"title":"Fast Matching Algorithm for Sparse Star Points Based on Improved Delaunay Subdivision","authors":"Liu Yang, Miao Li, Xinpu Deng","doi":"10.1109/ISCEIC53685.2021.00031","DOIUrl":"https://doi.org/10.1109/ISCEIC53685.2021.00031","url":null,"abstract":"The image under the starry sky background lacks texture detail information. It is difficult to use visual features such as regional features, shape to achieve image registration, and the star map structure may be unknown. To address these issues, this paper proposes a fast matching algorithm for sparse star points based on the Delaunay subdivision, which uses the geometric topological structure between the star points to solve the image transformation parameters and achieve accurate registration. Experimental results show that this method can still perform correct registration even in the presence of noise, target points, rotation, and translation, or lack of star points in the star map. The average registration error of 50 sets of simulated star maps is 0.4791 pixels, and the average registration time is 3.5386 s, which can meet the requirements of registration accuracy and speed, realizes the combination of mathematical methods and graphics.","PeriodicalId":342968,"journal":{"name":"2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126811631","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}
Pub Date : 2021-08-01DOI: 10.1109/ISCEIC53685.2021.00035
Zhifeng Liu, Yejin Yan, Tianping Li, Tonghe Ding
In order to further improve the accuracy of small target detection, this paper proposes a novel YOLOv3 small target detection method for multi-scale networks, which is mainly divided into four modules: 1. K-Means++ clustering algorithm to select anchor frames and accelerate model convergence; 2. multi- scale adaptive fusion to extract features and enhance network processing information; 3. end-to-end detection for network prediction to improve detection speed; 4. threshold score for ranking and using NMS to filter local maxima and output the predicted bounding box. Training and testing were conducted on the CCTSDB traffic sign dataset, and experiments showed that the algorithm significantly improved the detection accuracy of small targets compared with the original YOLOv3.
{"title":"A Multi-scale Network-based Method for the YOLOv3 Small Target Detection","authors":"Zhifeng Liu, Yejin Yan, Tianping Li, Tonghe Ding","doi":"10.1109/ISCEIC53685.2021.00035","DOIUrl":"https://doi.org/10.1109/ISCEIC53685.2021.00035","url":null,"abstract":"In order to further improve the accuracy of small target detection, this paper proposes a novel YOLOv3 small target detection method for multi-scale networks, which is mainly divided into four modules: 1. K-Means++ clustering algorithm to select anchor frames and accelerate model convergence; 2. multi- scale adaptive fusion to extract features and enhance network processing information; 3. end-to-end detection for network prediction to improve detection speed; 4. threshold score for ranking and using NMS to filter local maxima and output the predicted bounding box. Training and testing were conducted on the CCTSDB traffic sign dataset, and experiments showed that the algorithm significantly improved the detection accuracy of small targets compared with the original YOLOv3.","PeriodicalId":342968,"journal":{"name":"2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127456114","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}
Pub Date : 2021-08-01DOI: 10.1109/ISCEIC53685.2021.00027
Kaicheng Zhang, J. Yang
This paper studies the monitoring of ADS-B signals based on spectrum and signal decoding. Firstly, one receiver is used to collect 1089.5MHz -1090.5MHz spectrum data, and the other is used to decode ADS-B (Automatic Dependent Surveillance-Broadcast) radio signal to obtain aircraft flight height, position, speed and other data; Secondly, store the data in the database and perform k-means clustering on the ADS-B spectrum data to determine whether there is a signal, and display the flight trajectory on the ArcGIS Map. Finally, a spark experimental system was built to demonstrate the above process. The flight data of the domestic Ctrip website was crawled for statistical analysis. The system has functions such as three-dimensional flight display, real-time trajectory tracking, and signal detection.
{"title":"Collection, analysis and display of civil aviation data based on Spark","authors":"Kaicheng Zhang, J. Yang","doi":"10.1109/ISCEIC53685.2021.00027","DOIUrl":"https://doi.org/10.1109/ISCEIC53685.2021.00027","url":null,"abstract":"This paper studies the monitoring of ADS-B signals based on spectrum and signal decoding. Firstly, one receiver is used to collect 1089.5MHz -1090.5MHz spectrum data, and the other is used to decode ADS-B (Automatic Dependent Surveillance-Broadcast) radio signal to obtain aircraft flight height, position, speed and other data; Secondly, store the data in the database and perform k-means clustering on the ADS-B spectrum data to determine whether there is a signal, and display the flight trajectory on the ArcGIS Map. Finally, a spark experimental system was built to demonstrate the above process. The flight data of the domestic Ctrip website was crawled for statistical analysis. The system has functions such as three-dimensional flight display, real-time trajectory tracking, and signal detection.","PeriodicalId":342968,"journal":{"name":"2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC)","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127499415","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}
Pub Date : 2021-08-01DOI: 10.1109/ISCEIC53685.2021.00013
B. Chen, G. Fu
Infantile hemangioma is one of the most common benign tumors, which appears in the early stages of life, most of which can be cured automatically, but some serious cases can threaten the normal growth and even life of the baby. Therefore, making timely and correct risk ratings for the status of hemangioma is extremely important for the treatment of patients. At present, this work is mainly done manually by pediatricians with high professional quality. This study proposes a deep learning-based method to rank infant hemangioma risk, which is divided into three levels: high risk, medium risk and low risk. This article describes a hemangioma risk classifier based on a convolutional neural network structure to achieve an assessment of the risk of hemangioma for auxiliary diagnosis. The challenge is how to achieve good classification on a relatively small data set, which contains 1032 images from 344 different patients. The final result is promising, according to the performance evaluation of the model, the accuracy on the test set reaches 90.85%.
{"title":"Risk Rating of Infantile Hemangioma using Deep Learning","authors":"B. Chen, G. Fu","doi":"10.1109/ISCEIC53685.2021.00013","DOIUrl":"https://doi.org/10.1109/ISCEIC53685.2021.00013","url":null,"abstract":"Infantile hemangioma is one of the most common benign tumors, which appears in the early stages of life, most of which can be cured automatically, but some serious cases can threaten the normal growth and even life of the baby. Therefore, making timely and correct risk ratings for the status of hemangioma is extremely important for the treatment of patients. At present, this work is mainly done manually by pediatricians with high professional quality. This study proposes a deep learning-based method to rank infant hemangioma risk, which is divided into three levels: high risk, medium risk and low risk. This article describes a hemangioma risk classifier based on a convolutional neural network structure to achieve an assessment of the risk of hemangioma for auxiliary diagnosis. The challenge is how to achieve good classification on a relatively small data set, which contains 1032 images from 344 different patients. The final result is promising, according to the performance evaluation of the model, the accuracy on the test set reaches 90.85%.","PeriodicalId":342968,"journal":{"name":"2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132145051","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}
Pub Date : 2021-08-01DOI: 10.1109/ISCEIC53685.2021.00045
Shiyong Xiong, Yang Yan, Ai-rong Xie
The dynamic range of the imaging device represents its ability to capture bright and dark targets in the scene. Limited by the hardware, the dynamic range of a single imaging will lead the loss of information like over-exposed or under-exposed, which makes the look and feel of the imaging result unsatisfactory. Although the dynamic range of imaging can be expanded through multi-exposure fusion, there is risk to produce artifacts such as halos. To address the above issue, an Anisotropic Convolutional Block based on convolutional neural networks is proposed, which can inhibit the halo among the edges with high contrast. At the same time, a fusion strategy based on image structure similarity and pixel intensity is proposed, which can improve the visual perception of imaging results. Experimental results prove that the proposed method can effectively improve the quality of high dynamic range imaging.
{"title":"Multiple-Exposure Fusion with Halo-Free Convolutional Neural Network","authors":"Shiyong Xiong, Yang Yan, Ai-rong Xie","doi":"10.1109/ISCEIC53685.2021.00045","DOIUrl":"https://doi.org/10.1109/ISCEIC53685.2021.00045","url":null,"abstract":"The dynamic range of the imaging device represents its ability to capture bright and dark targets in the scene. Limited by the hardware, the dynamic range of a single imaging will lead the loss of information like over-exposed or under-exposed, which makes the look and feel of the imaging result unsatisfactory. Although the dynamic range of imaging can be expanded through multi-exposure fusion, there is risk to produce artifacts such as halos. To address the above issue, an Anisotropic Convolutional Block based on convolutional neural networks is proposed, which can inhibit the halo among the edges with high contrast. At the same time, a fusion strategy based on image structure similarity and pixel intensity is proposed, which can improve the visual perception of imaging results. Experimental results prove that the proposed method can effectively improve the quality of high dynamic range imaging.","PeriodicalId":342968,"journal":{"name":"2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131855643","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}
Pub Date : 2021-08-01DOI: 10.1109/ISCEIC53685.2021.00036
Cong Wang, Yuancheng Zhao, Jianhu Dong
Electronic data forensics is the process of obtaining, preserving, analyzing and presenting evidence for computer invasion, destruction, fraud, attack and other criminal acts. Some key digital evidence of cybercrime exists in physical memory or stored in page exchange files, so memory forensics is an important part of electronic data forensics. This paper studies RAM-based electronic data forensics with the use of the memory forensics tool Volatility. By obtaining the memory data of real equipment, cloud computing, virtual machine or virtual devices, performing the extraction and analysis of process information, registry, network connection, strings, access records and other contents, and extracting the digital evidence related to network attack or network crime.
{"title":"Research on Electronic Data Forensics Based on RAM","authors":"Cong Wang, Yuancheng Zhao, Jianhu Dong","doi":"10.1109/ISCEIC53685.2021.00036","DOIUrl":"https://doi.org/10.1109/ISCEIC53685.2021.00036","url":null,"abstract":"Electronic data forensics is the process of obtaining, preserving, analyzing and presenting evidence for computer invasion, destruction, fraud, attack and other criminal acts. Some key digital evidence of cybercrime exists in physical memory or stored in page exchange files, so memory forensics is an important part of electronic data forensics. This paper studies RAM-based electronic data forensics with the use of the memory forensics tool Volatility. By obtaining the memory data of real equipment, cloud computing, virtual machine or virtual devices, performing the extraction and analysis of process information, registry, network connection, strings, access records and other contents, and extracting the digital evidence related to network attack or network crime.","PeriodicalId":342968,"journal":{"name":"2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134425009","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}
Pub Date : 2021-08-01DOI: 10.1109/ISCEIC53685.2021.00069
Pei Zhang, Chengye Zhang, Weilong Gai
Because unmanned combat platforms can enhance combat capabilities and expand combat areas, they can minimize casualties and can play an important role in wars. With the increasing application of unmanned combat platforms, the need for multi-domain coordinated operations in land, sea, and air has become prominent. The combat effectiveness of the traditional single-platform and single-area combat model is extremely limited and no longer meets the needs of warfare. Therefore, the unmanned combat platforms combat mode of the company has gradually developed from a single platform to a more flexible multi-platform cluster combat. How to achieve multi-domain coordinated operations of unmanned combat platforms in the air, ground, and sea is the key to achieve combat missions and enhance combat capabilities. This article defines the concept of multi-domain coordinated operations for unmanned combat platforms, and discusses the multi-domain coordinated operations of unmanned combat platforms. Research on the application and development trend of coordinated operations has important military strategic significance.
{"title":"Research on Application and Development Trend of Multi-domain Cooperative Combat for Unmanned Combat Platform","authors":"Pei Zhang, Chengye Zhang, Weilong Gai","doi":"10.1109/ISCEIC53685.2021.00069","DOIUrl":"https://doi.org/10.1109/ISCEIC53685.2021.00069","url":null,"abstract":"Because unmanned combat platforms can enhance combat capabilities and expand combat areas, they can minimize casualties and can play an important role in wars. With the increasing application of unmanned combat platforms, the need for multi-domain coordinated operations in land, sea, and air has become prominent. The combat effectiveness of the traditional single-platform and single-area combat model is extremely limited and no longer meets the needs of warfare. Therefore, the unmanned combat platforms combat mode of the company has gradually developed from a single platform to a more flexible multi-platform cluster combat. How to achieve multi-domain coordinated operations of unmanned combat platforms in the air, ground, and sea is the key to achieve combat missions and enhance combat capabilities. This article defines the concept of multi-domain coordinated operations for unmanned combat platforms, and discusses the multi-domain coordinated operations of unmanned combat platforms. Research on the application and development trend of coordinated operations has important military strategic significance.","PeriodicalId":342968,"journal":{"name":"2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134316284","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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