Third International Seminar on Artificial Intelligence, Networking, and Information Technology最新文献_第6页

Design of gesture recognition system based on machine vision 基于机器视觉的手势识别系统设计

Third International Seminar on Artificial Intelligence, Networking, and Information Technology Pub Date : 2023-02-22 DOI: 10.1117/12.2667314

Weiquan Chen, Jichao Yan, Shufen Huang, L.G. Tan

引用次数: 0

Emotion recognition of multimodal face images based on convolutional neural network 基于卷积神经网络的多模态人脸图像情感识别

Third International Seminar on Artificial Intelligence, Networking, and Information Technology Pub Date : 2023-02-22 DOI: 10.1117/12.2667333

Minli Wen

{"title":"Emotion recognition of multimodal face images based on convolutional neural network","authors":"Minli Wen","doi":"10.1117/12.2667333","DOIUrl":"https://doi.org/10.1117/12.2667333","url":null,"abstract":"In the background of changing angle and multi-dimensional posture overlapping, it is necessary to extract and recognize the emotion of multi-modal face images, so as to improve the expression ability of facial emotion. A method of emotion recognition of multi-modal face images under changing angle and multi-dimensional posture overlapping background based on convolution neural network and morphological feature parameter recognition is proposed. Constructing a face feature collection model with variable angle and multi-dimensional posture overlapping background, performing fusion filtering on the collected face images with variable angle and multi-dimensional posture overlapping background, extracting the edge contour feature quantity of the face images with variable angle and multi-dimensional posture overlapping background, and filtering and denoising the original image by using morphological convolution neural network transformation method, Multi-modal wavelet scale decomposition method is used to decompose the emotion features of multi-modal face images under the background of changing angles and multi-dimensional postures, and the detection model of pixel points and similarity features of multi-modal face images under the background of changing angles and multi-dimensional postures is constructed. Morphological convolution neural network transformation method is used to transform the emotion features of multi-modal face images, and edge corner detection and expression feature point clustering analysis are combined to realize the emotion recognition of multi-modal face images. The simulation results show that this method has good performance in feature extraction and clustering of multimodal facial image emotion recognition, good expression ability of facial emotion and high image quality.","PeriodicalId":128051,"journal":{"name":"Third International Seminar on Artificial Intelligence, Networking, and Information Technology","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126801429","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

Wind power prediction method based on multi-loop improved gradient boosting decision tree 基于多回路改进梯度增强决策树的风电功率预测方法

Third International Seminar on Artificial Intelligence, Networking, and Information Technology Pub Date : 2023-02-22 DOI: 10.1117/12.2667668

Zheng He, Lin Xu, Yufei Ai, Wei Li, Huanhuan Dong

{"title":"Wind power prediction method based on multi-loop improved gradient boosting decision tree","authors":"Zheng He, Lin Xu, Yufei Ai, Wei Li, Huanhuan Dong","doi":"10.1117/12.2667668","DOIUrl":"https://doi.org/10.1117/12.2667668","url":null,"abstract":"With the increase in energy demand, carbon emissions, environmental pollution, climate change and other issues have become increasingly prominent, China has accelerated the construction of new energy sources. Especially in the field of wind power generation, it is the most potential type of large-scale development of non-hydroelectric renewable energy. Due to the volatility, intermittency and low energy density of wind power, the power of wind power also fluctuates. However, with the early digital transformation of my country's energy industry, a large number of meteorological environments and equipment measurement points have been accumulated in wind power production sites. Power generation related data, using artificial intelligence, deep learning and other technologies can effectively predict the power generation of the station with high precision. A model algorithm of multi-loop gradient boosting decision tree is used in this paper, considering the stationarity test of time series and wind power fluctuation attribute, the accuracy of wind power prediction is effectively improved. Help the power dispatching department to pre-arrange dispatching plans according to wind power changes. Ensure the smooth and safe operation of the power grid.","PeriodicalId":128051,"journal":{"name":"Third International Seminar on Artificial Intelligence, Networking, and Information Technology","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131574864","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

Accelerating real-time music beat tracking based on hidden Markov model by using genre information 利用类型信息加速基于隐马尔可夫模型的实时音乐节拍跟踪

Third International Seminar on Artificial Intelligence, Networking, and Information Technology Pub Date : 2023-02-22 DOI: 10.1117/12.2667472

Liangfeng Zhou, Guangxiao Song, Zhi-jian Wang, Meng Xia

{"title":"Accelerating real-time music beat tracking based on hidden Markov model by using genre information","authors":"Liangfeng Zhou, Guangxiao Song, Zhi-jian Wang, Meng Xia","doi":"10.1117/12.2667472","DOIUrl":"https://doi.org/10.1117/12.2667472","url":null,"abstract":"The essence of enjoying music is that people can track music beat anytime and be brought into the scene expressed by music. Music beat tracking is a common task in Music Information Retrieve (MIR). While numerous studies have been done in this field, most works focus on the offline beat tracking. However, tracking music beat in real time is a challenging task for computers. In the past few years, people attach more importance to this field. Researchers care about the music beat without taking music style or context into consideration. In this paper, we propose a method for tracking music beats in real time in conjunction with music genre. Specifically, the proposed model is based on a widely-used framework of Hidden Markov Model (HMM). By recognizing the genre of input music, we narrow the range of beats per minute (BPM), which significantly reduces the number of hidden states in HMM. Consequently, the inference time of beat tracking decreases. We experimentally verify the model on the open-source Ballroom dataset, and its accuracy remains at a competitive level while having a much shorter inference time.","PeriodicalId":128051,"journal":{"name":"Third International Seminar on Artificial Intelligence, Networking, and Information Technology","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134433792","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

Advantage policy update based on proximal policy optimization 基于近端策略优化的优势策略更新

Third International Seminar on Artificial Intelligence, Networking, and Information Technology Pub Date : 2023-02-22 DOI: 10.1117/12.2667235

Zilin Zeng, Junwei Wang, Zhigang Hu, Dongnan Su, Peng Shang

引用次数: 0

Target scale information detection based on improved Faster R-CNN 基于改进Faster R-CNN的目标尺度信息检测

Third International Seminar on Artificial Intelligence, Networking, and Information Technology Pub Date : 2023-02-22 DOI: 10.1117/12.2667260

Yu Liu, Zhiqiang Wang, Fengjing Zhang, Jun Xie, Zhaohong Xu

引用次数: 0

DOA estimation of rail transit tunnel far field signals based on reconstructive subspace MUSIC 基于重构子空间MUSIC的轨道交通隧道远场信号DOA估计

Third International Seminar on Artificial Intelligence, Networking, and Information Technology Pub Date : 2023-02-22 DOI: 10.1117/12.2667279

Yanliang Jin, Rukun Lyu, Yuan Gao, Guoxing Zheng

{"title":"DOA estimation of rail transit tunnel far field signals based on reconstructive subspace MUSIC","authors":"Yanliang Jin, Rukun Lyu, Yuan Gao, Guoxing Zheng","doi":"10.1117/12.2667279","DOIUrl":"https://doi.org/10.1117/12.2667279","url":null,"abstract":"For the rail traffic, feasibility of 5th Generation (5G) mobile communication massive Multiple Input Multiple Output (MIMO) used in the tunnel is studying. In order to effectively set up base station, antenna and intelligent reflecting surface (IRS), the direction of arrival (DOA) must be captured. Aiming at the problem of poor performance of two-dimensional MUltiple SIgnal Classification (2D-MUSIC) algorithm in the environment of low signal-to-noise ratio (SNR), small snapshots and small incident angle interval signals, an improved MUSIC algorithm with uniform rectangular array (URA) based on reconstructive subspace is proposed. By reconstructing subspace, a new spatial spectrum is obtained in terms of subspace eigenvectors. Then, the DOAs are obtained by searching the maximum of the new spatial spectrum. High estimation accuracy and angular resolution are often required in practical applications of rail traffic 5G system, and there exist tunnel scenarios that we need the improved MUSIC algorithm has the ability to conduct two-dimensional DOA estimation. Simulations and the measured data of straight tunnel scenario are used to verify the effectiveness of the proposed algorithm and its higher searching precision in complex signal environments such as low SNR, strong-to-weak proximity, and coherent interference.","PeriodicalId":128051,"journal":{"name":"Third International Seminar on Artificial Intelligence, Networking, and Information Technology","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132144386","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

Research on feature extraction algorithm based on meta-learning 基于元学习的特征提取算法研究

Third International Seminar on Artificial Intelligence, Networking, and Information Technology Pub Date : 2023-02-22 DOI: 10.1117/12.2667413

Yanliang Jin, Baorong Fan, Yuan Gao

{"title":"Research on feature extraction algorithm based on meta-learning","authors":"Yanliang Jin, Baorong Fan, Yuan Gao","doi":"10.1117/12.2667413","DOIUrl":"https://doi.org/10.1117/12.2667413","url":null,"abstract":"Feature extraction is an important research topic in the field of image processing.In autonomous driving, it is of great importance to extract the feature information of the picture obtained by the vehicle camera for the agent to better understand the environment information. In order to improve the quality of feature extraction, this paper combines meta-learning and deep learning-based feature extraction methods, and proposes a Meta-VAE-WGAN-GP (MVWP) feature extraction algorithm, and applies it to automatic driving. Firstly, aiming at the problem of parameter centralization in Wasserstein generative adversarial network (WGAN) and the problem of gradient explosion and gradient disappearance caused by improper manual parameter adjustment, a generative adversarial network based on gradient penalty and Wasserstein distance (WGAN-GP) was proposed, and it was combined with VAE. The VAE-WGAN-GP model is formed. Secondly, aiming at the problem that the feature extraction model needs to be trained from scratch every time it is faced with a new task, and the training time is too long, the MVWP model is formed by combining meta-learning with VAE-WGAN-GP (VWP) mentioned above. Finally, the experimental results show that compared with VAE, VAE-WGAN and VWP, the training speed of MVWP model is increased by about 6 times, the reconstruction loss is reduced by 55.9%, 37.8% and 20.2%, respectively, and the reconstructed images are clearer.","PeriodicalId":128051,"journal":{"name":"Third International Seminar on Artificial Intelligence, Networking, and Information Technology","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124890456","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

Analysis of maritime unmanned combat cluster employment in the context of anti-intervention/area denial 反干涉/区域拒止背景下海上无人作战集群部署分析

Third International Seminar on Artificial Intelligence, Networking, and Information Technology Pub Date : 2023-02-22 DOI: 10.1117/12.2667516

Jiangshan Liu, P. Pen

{"title":"Analysis of maritime unmanned combat cluster employment in the context of anti-intervention/area denial","authors":"Jiangshan Liu, P. Pen","doi":"10.1117/12.2667516","DOIUrl":"https://doi.org/10.1117/12.2667516","url":null,"abstract":"With the new operational styles such as mosaic warfare and multi-domain warfare of the US military moving from concept to application, the winning elements and operational modes of future maritime operations have been profoundly changed. Firstly, the military capabilities of the US military to break through anti-access/area denial are analyzed, and then the characteristics and effects of the implementation of multi-domain warfare under the mosaic warfare concept in breaking through anti-access/area denial are extracted from the military capabilities, operational styles, and practical applications. On this basis, countermeasure suggestions are proposed to deal with the implementation of multi-domain warfare under the mosaic warfare concept. The practical significance of building unmanned maritime combat clusters is explained from the perspective of military needs, and the force design, equipment development, and combat style of unmanned maritime combat clusters are described in detail. A typical combat scenario is used to show the combat process of unmanned maritime combat clusters. Finally, the key problem model of intelligent command and control decision of maritime unmanned cluster is established for this typical combat scenario, and the corresponding algorithmic framework is constructed for the input and output of the typical combat scenario, which provides research ideas for further empirical research.","PeriodicalId":128051,"journal":{"name":"Third International Seminar on Artificial Intelligence, Networking, and Information Technology","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127893662","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

Technology research of micro air-launched decoy 微型空射诱饵技术研究

Third International Seminar on Artificial Intelligence, Networking, and Information Technology Pub Date : 2023-02-22 DOI: 10.1117/12.2667665

Fang-zheng Zhao, Xiao Zhang, Xin Zhang

引用次数: 0