International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)最新文献_第9页

Enhancing audio perception in augmented reality: a dynamic vocal information processing framework 增强增强现实中的音频感知：动态人声信息处理框架

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014440

Danqing Zhao, Shuyi Xin, Lechen Liu, Yihan Sun, Anqi Du

{"title":"Enhancing audio perception in augmented reality: a dynamic vocal information processing framework","authors":"Danqing Zhao, Shuyi Xin, Lechen Liu, Yihan Sun, Anqi Du","doi":"10.1117/12.3014440","DOIUrl":"https://doi.org/10.1117/12.3014440","url":null,"abstract":"The development of the Metaverse nowadays has sparked widespread emotions among researchers, and correspondingly, many technologies have been derived to improve the human's sense of reality in the Metaverse. Especially, Extended Reality (XR), as an indispensable and important technology and research direction in the study of the metaverse, aims to bring seamless transformation between the virtual world and the real-world immersion to the experiential world. However, the technology we currently lack is the ability to simultaneously separate, classify, and locate dynamic human sound information to enhance human sound perception in complex noise environments. This article proposes a framework that utilizes FCNN for separation, algebraic models for positioning to obtain estimated distances, and SVM for classification. The dataset is built to simulates distance-related changes with accurate ground truth labels. The results show that our method can effectively separate, separate, and locate mixed sound data, providing users with comprehensive information about the content, gender, and distance of the speaking object in complex sound environments, enhancing their immersive experience and perception ability. Our innovation lies in the combination of three audio processing technologies and the framework proposed may well inspire future work on related topics.","PeriodicalId":516634,"journal":{"name":"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)","volume":" 22","pages":"129691Z - 129691Z-9"},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139640520","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 automatic scoring algorithm for English composition based on machine learning 基于机器学习的英语作文自动评分算法研究

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014482

Hui Li

{"title":"Research on automatic scoring algorithm for English composition based on machine learning","authors":"Hui Li","doi":"10.1117/12.3014482","DOIUrl":"https://doi.org/10.1117/12.3014482","url":null,"abstract":"It is difficult to extract deep semantic features for English composition scoring methods based on artificial features, and it is difficult for English composition scoring methods based on neural networks to extract shallow features such as the number of words, resulting in the limitations of different composition scoring methods. Based on existing research results, this paper proposes an English composition scoring method that combines artificial feature extraction methods and deep learning methods. This method uses artificially designed features to extract shallow features at the word and sentence levels in the composition, draws on existing methods to extract semantic features of the composition, and performs regression calculations on the deep features and shallow features to obtain the total score of the composition. The experiment uses the Pearson evaluation index to measure the correlation between the predicted total score of the essay and the true total score under the combination method. The experiment shows that compared with the average results of 0.747 and 0.645 of baseline models such as BiLSTM and RNN, the algorithm proposed in this article is respectively improvements are 0.068 and 0.17, which proves the effectiveness of the method proposed in this paper.","PeriodicalId":516634,"journal":{"name":"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)","volume":"20 6","pages":"129690T - 129690T-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139640403","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 the simplification of building complex model under multi-factor constraints 多因素约束下建筑复杂模型的简化研究

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014388

Haoyuan Bai, Kelong Yang, Shunhua Liao

引用次数: 0

Three-dimensional target detection algorithm for dangerous goods in CT security inspection CT 安全检查中危险品的三维目标检测算法

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014353

Jingze He, Yao Guo, qing song

引用次数: 0

Research on collaborative positioning of intelligent vehicle aided navigation based on computer vision technology 基于计算机视觉技术的智能车辆辅助导航协同定位研究

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014415

Shun Zhang

引用次数: 0

Image segmentation of rail surface defects based on fractional order particle swarm optimization 2D-Otsu algorithm 基于分数阶粒子群优化 2D-Otsu 算法的轨道表面缺陷图像分割

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014444

Na Geng, Hu Sheng, Weizhi Sun, Yifeng Wang, Tan Yu, Zihan Liu

引用次数: 0

Microexpression recognition algorithm based on multi feature fusion 基于多特征融合的微表情识别算法

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014469

BaiYang Xiang, BoKai Li, Huaijuan Zang, Zeliang Zhao, Shu Zhan

引用次数: 0

Rapid identification of adulterated rice using fusion of near-infrared spectroscopy and machine vision data: the combination of feature optimization and nonlinear modeling 利用近红外光谱和机器视觉数据的融合快速识别掺假大米：特征优化与非线性建模的结合

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014380

Chenxuan Song, Jinming Liu, Chunqi Wang, Zhijiang Li

{"title":"Rapid identification of adulterated rice using fusion of near-infrared spectroscopy and machine vision data: the combination of feature optimization and nonlinear modeling","authors":"Chenxuan Song, Jinming Liu, Chunqi Wang, Zhijiang Li","doi":"10.1117/12.3014380","DOIUrl":"https://doi.org/10.1117/12.3014380","url":null,"abstract":"Rice is susceptible to mold and mildew during storage. Metabolites such as aflatoxin produced during mildew will do great harm to consumers. To meet the need for rapid detection of normal rice adulterated with moldy rice, a rapid identification method of adulterated rice was established based on data fusion of near-infrared spectroscopy and machine vision. Using competitive adaptive reweighted sampling (CARS), genetic algorithm (GA), and least angle regression (LARS) for spectral and image feature extraction, combined with support vector classification (SVC), random forest (RF), and gradient boosting tree (GBT) nonlinear discriminant models, and use Bayesian search to optimize modeling parameters. The results show that the GBT fusion data model established by LARS optimization of spectral and image feature variables has the highest discrimination accuracy, with recognition accuracy rates of 100.00% and 98.11% for its training and testing sets, respectively. The discrimination performance is significantly improved compared to single near-infrared spectroscopy and machine vision. The results indicate that rapid identification of adulterated rice based on near-infrared spectroscopy and machine vision data fusion technology is feasible, providing theoretical support for the development of online identification equipment for adulterated rice.","PeriodicalId":516634,"journal":{"name":"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)","volume":"63 2","pages":"129692J - 129692J-16"},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140511309","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

Fast and high quality neural radiance fields reconstruction based on depth regularization 基于深度正则化的快速、高质量神经辐射场重建

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014528

Bin Zhu, Gaoxiang He, Bo Xie, Yi Chen, Yaoxuan Zhu, Liuying Chen

引用次数: 0

Combinatorial action recognition based on causal segment intervention 基于因果片段干预的组合动作识别

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014465

Xiaozhou Sun

引用次数: 0