International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)最新文献_第7页

Design of automatic identification algorithm for double-feature fault signal waveform of power equipment 电力设备双特征故障信号波形的自动识别算法设计

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014372

Huidong Tang, Duo Li, Wendong Lei, Jinpeng Meng

{"title":"Design of automatic identification algorithm for double-feature fault signal waveform of power equipment","authors":"Huidong Tang, Duo Li, Wendong Lei, Jinpeng Meng","doi":"10.1117/12.3014372","DOIUrl":"https://doi.org/10.1117/12.3014372","url":null,"abstract":"The conventional automatic identification algorithm of double-feature fault signal waveform of power equipment mainly uses ART (Adaptive Resonnance Theory) network for classification and discrimination, which is easily influenced by the identification mapping relationship, resulting in low correct identification rate of fault signal waveform. Therefore, it is necessary to design a brand-new automatic identification algorithm of double-feature fault signal waveform of power equipment. That is to say, the waveform characteristics of dual-feature fault signal of power equipment are extracted, and the optimization algorithm for automatic identification of dual-feature fault signal waveform of power equipment is generated, so that the automatic identification of fault signal waveform is realized. The experimental results show that the designed double-feature fault signal waveform automatic identification algorithm for power equipment has a high correct fault identification rate, which proves that the designed double-feature fault signal waveform automatic identification algorithm for power equipment has good identification effect, reliability and certain application value, and has made certain contributions to improving the operation safety of power equipment.","PeriodicalId":516634,"journal":{"name":"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)","volume":"16 4","pages":"1296903 - 1296903-7"},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140511387","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

Lightweight person re-identification model employing symmetrical combination units 采用对称组合单元的轻量级人员再识别模型

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014389

dawei cai, qingwei tang

{"title":"Lightweight person re-identification model employing symmetrical combination units","authors":"dawei cai, qingwei tang","doi":"10.1117/12.3014389","DOIUrl":"https://doi.org/10.1117/12.3014389","url":null,"abstract":"As an image retrieval problem, person re-identification (Re-ID) relies on robust features extracted by convolution neural models. Most current methods use large backbone models for feature extraction (e.g., ResNet50). However, these large backbone models have many parameters, which cause many problems when embedded in smart camera devices. For example, the device's computing resources are limited, the real-time operation speed is limited, etc. So it is necessary to construct models with low parameters and low complexity. This paper proposes a new lightweight baseline for Re-ID, which is SCL-net and all underlying modules of the model are reconstructed. In our work, we design a new convolution unit----symmetrical combination units (SC-unit), which construct features map of richer channels by reusing feature maps from different convolution layers. In addition, we redesigned all the base modules of SCL-net and proved the effectiveness of all modules. We joint training of shallow and deep features of the model respectively to improve the accuracy of the model. Our SCL-net has about 2.3M parameters, and it can achieve 95.2%/85.9% on Rank-1 and mAP without any pretraining.","PeriodicalId":516634,"journal":{"name":"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)","volume":"16 2","pages":"129692O - 129692O-11"},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140511389","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 electrical contact performance based on machine vision 基于机器视觉的电接触性能研究

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014355

Chun-lin Li, Yangxin Ou, Lei You, Zewu Zhang

引用次数: 0

Research and implementation of efficient retrieval algorithm in big data environment 大数据环境下高效检索算法的研究与实现

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014436

pan gao, Shuhua shao

{"title":"Research and implementation of efficient retrieval algorithm in big data environment","authors":"pan gao, Shuhua shao","doi":"10.1117/12.3014436","DOIUrl":"https://doi.org/10.1117/12.3014436","url":null,"abstract":"Under the background of digital information age, faced with the increasing data scale and complexity, the application limitations of traditional centralized retrieval services are becoming more and more obvious, and it is urgent to improve the data structure expansion, incremental update control and retrieval operation efficiency. In this paper, the efficient retrieval algorithm and technology of massive data information are taken as the research object, and a set of construction scheme of big data storage and retrieval system is proposed for unstructured data, which promotes the organic combination of distributed technology and full-text retrieval technology and realizes the optimization of fast retrieval processing mode of large-scale data. The system is based on Hadoop framework, with Hbase as the data storage module, and combined with ElasticSearch engine, IKAnalyzer word breaker and Redis cache to complete real-time and efficient data retrieval. Finally, based on Java web technology, a network application program convenient for users to operate online is formed. Practice has proved that the system has solved many problems in the process of collecting, storing and retrieving massive unstructured text data. At the same time, it improves the sharing transmission efficiency and concurrent access control ability of data information, and opens up a brand-new big data retrieval service model.","PeriodicalId":516634,"journal":{"name":"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)","volume":"24 4","pages":"129690H - 129690H-4"},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140511995","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

Image recognition method for dangerous behavior of non-stop construction personnel in large airports 大型机场不停航施工人员危险行为的图像识别方法

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014586

Zhenyu Zhao, Liangsui Geng

引用次数: 0

Multitarget detection of assembly parts based on improved YOLOv7 基于改进型 YOLOv7 的装配部件多目标检测

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014468

Jinhao Wang, Jizhuang Hui, Yaqian Zhang, Tao Zhou, Kai Ding

引用次数: 0

Research on surface defect classification method of hot rolled strip steel based on comparative learning 基于比较学习的热轧带钢表面缺陷分类方法研究

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014479

Xingshuai Zang, Shengnan Zhang, Yu He

引用次数: 0

An improved dung beetle optimizer 改进的蜣螂优化器

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014472

Jinxiang Feng, Jingyang Li, Yufeng Zhang, H. Baoyin

{"title":"An improved dung beetle optimizer","authors":"Jinxiang Feng, Jingyang Li, Yufeng Zhang, H. Baoyin","doi":"10.1117/12.3014472","DOIUrl":"https://doi.org/10.1117/12.3014472","url":null,"abstract":"Dung Beetle Optimizer(DBO) is an effective metaheuristic algorithm proposed in 2022. But at the same time, DBO also suffers from a local-global imbalance in the exploration process, tends to fall into local optimization and exploitability needs to be further improved, etc. Therefore, we propose an improved DBO algorithm to address these shortcomings and named it CDBO. Firstly, Tent chaotic mapping can be used for the purpose of initializing the population, improving the quality of initial solutions, promoting the enhancement of population variety, and augmenting the global search capability of the algorithm. Secondly, introducing dynamic weighting factors enables the algorithm to fully search for local areas while also taking into account global exploration. To assess the effectiveness of CDBO, a total of 12 benchmark test functions were utilized to evaluate the performance of this algorithm, wherein CDBO was compared with other widely recognized metaheuristic algorithms. The results showed that CDBO had improved search accuracy and convergence speed. Finally, CDBO was applied to airfoil optimization problem, verifying the feasibility of applying CDBO to practical engineering problems.","PeriodicalId":516634,"journal":{"name":"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)","volume":"9 2","pages":"129692V - 129692V-9"},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140511670","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

Multi-objective vehicle routing problem with time windows under uncertain conditions 不确定条件下带有时间窗口的多目标车辆路线问题

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014402

jiashuo guo, Yuxin Liu

引用次数: 0

Design and realization of cross-border e-commerce logistics intelligent monitoring and early warning system based on improved genetic algorithm 基于改进遗传算法的跨境电商物流智能监测预警系统的设计与实现

International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023) Pub Date : 2024-01-09 DOI: 10.1117/12.3014648

Fei Lei, Zicen Liao, Mingxiu Huang, Hui Tian

{"title":"Design and realization of cross-border e-commerce logistics intelligent monitoring and early warning system based on improved genetic algorithm","authors":"Fei Lei, Zicen Liao, Mingxiu Huang, Hui Tian","doi":"10.1117/12.3014648","DOIUrl":"https://doi.org/10.1117/12.3014648","url":null,"abstract":"The rapid development of the cross-border e-commerce market has led to an increase in logistics complexity, and intelligent monitoring and early warning systems are needed to meet the challenges. The objective of this study is to design and implement a cross-border e-commerce logistics monitoring and early warning system based on improved genetic algorithms to enhance the reliability of transportation quality. The system collects data related to cross-border e-commerce logistics transportation quality, analyzes and optimizes the improved genetic algorithm in one system, and uses the improved genetic algorithm for decision-making and planning. The system has a real-time monitoring function to discover potential transportation quality problems and conduct predictive analysis to identify the min advance for timely warning. The system can provide cross-border e-commerce enterprises with more efficient logistics and transportation quality management, reduce costs and improve customer satisfaction. It helps enterprises to cope with logistics challenges, provide more reliable services, and promote the continuous development and prosperity of cross-border e-commerce.","PeriodicalId":516634,"journal":{"name":"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)","volume":"58 1","pages":"129690W - 129690W-4"},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140511632","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