2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC)最新文献

Intelligent Recognition Translation Optimization Algorithm Based on Machine Vision 基于机器视觉的智能识别翻译优化算法

2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2022-04-14 DOI: 10.1109/IPEC54454.2022.9777572

Ruichao Li

{"title":"Intelligent Recognition Translation Optimization Algorithm Based on Machine Vision","authors":"Ruichao Li","doi":"10.1109/IPEC54454.2022.9777572","DOIUrl":"https://doi.org/10.1109/IPEC54454.2022.9777572","url":null,"abstract":"At this stage, machine vision (MV) technology is developing rapidly, and good results have been achieved in the fields of text recognition, image processing, and natural language processing. Intelligent recognition translation, as an efficient tool, can perform equivalent conversions between different languages, while still maintaining the original semantics, which has important practical significance. Based on this, the purpose of this article is to study the MV - based intelligent recognition translation optimization algorithm. This article proposes a text recognition method based entirely on convolutional neural networks, incorporates attention mechanism, introduces LSTM with \"forgetting\" function, and introduces the specific structure of a fully convolutional sequence decoder. This article designs an intelligent recognition and translation system, and introduces the end-to-end recognition and translation module. Experimental data shows that the BLUE values of the method in this paper are 25.57, 25.63, and 25.71, respectively. This shows that the method in this paper has a good effect in text recognition and translation.","PeriodicalId":232563,"journal":{"name":"2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115758323","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

Detection of Power Line Insulator Based on Enhanced YOLO Model 基于增强YOLO模型的电力线绝缘子检测

2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2022-04-14 DOI: 10.1109/ipec54454.2022.9777398

Yanbo Cheng

{"title":"Detection of Power Line Insulator Based on Enhanced YOLO Model","authors":"Yanbo Cheng","doi":"10.1109/ipec54454.2022.9777398","DOIUrl":"https://doi.org/10.1109/ipec54454.2022.9777398","url":null,"abstract":"As a special insulation device, insulators play an important role in aerial transmission lines. It can be easily influenced by the wind load, snow load and wire swing in severe weather. The fault of the insulator will seriously affect and destroy the safety and normal operation of the entire transmission line. Therefore, in the operation and inspection of the transmission line, the detection of insulator defects must be strengthened. Since the insulators are constructed in a complex environment and the background of the images collected by air is also extremely complicated, traditional defect detection methods rely on specific scenarios for specific analysis and the robustness is weak. Changes in scenes, changes in UAV’s shooting angles, and changes in lighting conditions will all make it difficult for the model to get good inspection results. This paper proposes an algorithm for locating and detecting insulator defects based on an enhanced YOLO model. Due to the electromagnetic interference during the power inspection of the UAV, there is a certain amount of noise in the image of the aerial insulator. At the same time, in order to solve the problem of few shots which leads to training difficulty, this paper uses a variety of data augmentation, including affine transformation, Gaussian blur processing, gray scale transformation, brightness and contrast transformation and random erasing of pixels, and then the augmentation data is used to train different YOLO models. The results show that the detection algorithm based on the YOLO model meets the robustness and accuracy of insulator defect detection, and augmented experiment results are better than those of the conventional YOLOs in power line insulator defect detection tasks.","PeriodicalId":232563,"journal":{"name":"2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC)","volume":"23 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120818013","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: 5

Research and Analysis on Temperature Field and Electric Field of DC Cable 直流电缆温度场和电场的研究与分析

2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2022-04-14 DOI: 10.1109/IPEC54454.2022.9777518

Yubo Shen, M. Wu, Dewen Zhang, Hongyi Zhou, Minhu Xu, M. Gong, Kexin Zhang, Meng Zhou

引用次数: 0

Study on the Surface Roughness Improvement for Silicon Samples with Millimeter-Size Openings 毫米开孔硅样品表面粗糙度改善研究

2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2022-04-14 DOI: 10.1109/ipec54454.2022.9777438

Xiao Hu

引用次数: 0

Analysis and Design of Smart Cold Chain Logistics Simulation Model Based on Internet of Things Technology 基于物联网技术的智能冷链物流仿真模型分析与设计

2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2022-04-14 DOI: 10.1109/IPEC54454.2022.9777403

Xiaohua Cai, Hongzhen Zhang, Qiang Li

{"title":"Analysis and Design of Smart Cold Chain Logistics Simulation Model Based on Internet of Things Technology","authors":"Xiaohua Cai, Hongzhen Zhang, Qiang Li","doi":"10.1109/IPEC54454.2022.9777403","DOIUrl":"https://doi.org/10.1109/IPEC54454.2022.9777403","url":null,"abstract":"With the continuous improvement of people’s quality of life and tremendous changes in consumption concepts, people’s demand for fresh agricultural products is increasing, which has led to a huge gap in the supply of fresh agricultural products logistics. In recent years, frequent food quality and safety issues have attracted the attention of consumers and have been highly valued by the country, making enterprises deeply aware of the importance of the refrigeration supply chain. However, the traditional cold chain supply of agricultural products is far from being able to meet the strict quality requirements of food for consumers in terms of production, processing, storage, transportation and sales. Therefore, how to improve the efficiency of the product refrigeration supply chain, reduce logistics costs, and ensure product freshness and quality assurance has become the focus and difficulty of establishing a cold chain supply chain business. This article is based on the analysis and design of the intelligent cold chain logistics simulation model under the Internet of Things technology. Firstly, the literature research method is used to summarize the problems of the intelligent cold chain logistics under the Internet of Things technology and the advantages of the intelligent cold chain logistics under the Internet of Things technology. The feasibility of the intelligent cold chain logistics simulation model under the Internet of Things technology, and then through the analysis of the cold chain logistics process unit and organization, the modeling is carried out based on the analysis results.","PeriodicalId":232563,"journal":{"name":"2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114439971","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: 2

Experimental Teaching and Simulation System for Ship Energy Efficiency Management 船舶能效管理实验教学与仿真系统

2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2022-04-14 DOI: 10.1109/ipec54454.2022.9777366

Kejia Zhang, N. Chen, Wei Liu

引用次数: 0

Improved particle filter algorithm based on piezoelectric Lamb wave monitoring characteristics 基于压电Lamb波监测特性的改进粒子滤波算法

2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2022-04-14 DOI: 10.1109/ipec54454.2022.9777535

Zhang Hua, Ning Ning

{"title":"Improved particle filter algorithm based on piezoelectric Lamb wave monitoring characteristics","authors":"Zhang Hua, Ning Ning","doi":"10.1109/ipec54454.2022.9777535","DOIUrl":"https://doi.org/10.1109/ipec54454.2022.9777535","url":null,"abstract":"The prediction of fatigue crack growth by particle filter algorithm is to establish the state space-model of particle filter by using pairs formula combined with state noise model, to establish the observation space model of particle filter by using Lamb and its damage factor monitoring crack growth method combined with observation noise model, and to predict the crack growth by using the state-space model at the same time. In the process of monitoring fatigue crack growth by Lamb wave, the longer the crack is, the greater the uncertainty of the damage factor is. Based on the above characteristics, an observation space model with an observation noise model continuously modified with crack length is established. The hole edge crack propagation experiments are carried out to predict the crack propagation of particle filter algorithm and the improved particle filter algorithm. The experimental results show that the improved particle filter algorithm is not easy to diverge in the later stage of crack propagation, that is, after 25,000 cycles in this experiment. After 27650 cycles, the crack propagation prediction error is only 0.7mm.","PeriodicalId":232563,"journal":{"name":"2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128510735","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

The USV Path Planning of Dueling DQN Algorithm Based on Tree Sampling Mechanism 基于树形采样机制的决斗DQN算法USV路径规划

2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2022-04-14 DOI: 10.1109/IPEC54454.2022.9777508

Zhijian Huang, Sen Liu, Gui-chen Zhang

{"title":"The USV Path Planning of Dueling DQN Algorithm Based on Tree Sampling Mechanism","authors":"Zhijian Huang, Sen Liu, Gui-chen Zhang","doi":"10.1109/IPEC54454.2022.9777508","DOIUrl":"https://doi.org/10.1109/IPEC54454.2022.9777508","url":null,"abstract":"The path planning and obstacle avoidance of USV (unmanned surface vessel) has become a research hotspot in recent years. Among them, the DQN algorithm has achieved good results in the obstacle avoidance and path planning problems of unmanned surface vessel. However, the algorithm suffers from the problems that the sampling method does not make full use of the stored information and the randomness of action selection during the training process is too large and the convergence is too slow. In this paper, we propose a Dueling DQN algorithm to optimize obstacle avoidance and path planning, which based on tree sampling mechanism. The Dueling DQN algorithm will decomposes the value function Q into a state-value function (V) and a dominance function (A). Meanwhile, the absolute value of TD-error is directly used as a priority indicator for priority sampling in the sampling process. Subsequently, the network model is built and experiments are conducted on each of the four maps. As a result, the convergence steps and loss values of the proposed algorithm on the four paths are better than those of the DQN algorithm. It shows that the dueling DQN algorithm can effectively use the stored information for optimal path planning.","PeriodicalId":232563,"journal":{"name":"2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128690026","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: 3

Classification of Chinese Text in the Power Field Using FastText with Electric Power Keywords 基于快速文本的电力领域中文文本分类

2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2022-04-14 DOI: 10.1109/ipec54454.2022.9777517

Changan Li, Feihu Hu, Yanpeng Wang

{"title":"Classification of Chinese Text in the Power Field Using FastText with Electric Power Keywords","authors":"Changan Li, Feihu Hu, Yanpeng Wang","doi":"10.1109/ipec54454.2022.9777517","DOIUrl":"https://doi.org/10.1109/ipec54454.2022.9777517","url":null,"abstract":"Text classification has always been a hot research topic in the field of natural language processing. Fasttext is a model which is simple in structure and has the advantage of fast and efficient. In order to analyze the situation of electric power intellectual property in recent years, this paper use the model of FastText to process Chinese electric power core journals and patents in recent five years. The text information in the company's intellectual property rights is divided into a series of phrases representing individual meanings though word segmentation basing on the Jieba word segmentation tool. The stop words unrelated to the power industry in the phrases are removed, and the word related the power industry frequency corresponding to the phrases and the frequency of occurrence in the text are counted. According to the characteristics of power industry word aggregation, the phrase can be divided into 26 categories. The text classification model based on keywords of power industry was designed, and the machine learning algorithm Fasttext is used to complete the text classification. Based on each subdivision field of power, the publication situation of intellectual property is analyzed and counted, and the results of power system intellectual property are visualized.","PeriodicalId":232563,"journal":{"name":"2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126674721","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

Optimization Model of Agricultural Product Logistics Network Based on Internet Technology 基于互联网技术的农产品物流网络优化模型

2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) Pub Date : 2022-04-14 DOI: 10.1109/IPEC54454.2022.9777603

L. Tian

{"title":"Optimization Model of Agricultural Product Logistics Network Based on Internet Technology","authors":"L. Tian","doi":"10.1109/IPEC54454.2022.9777603","DOIUrl":"https://doi.org/10.1109/IPEC54454.2022.9777603","url":null,"abstract":"\"Internet +\" era has arrived, it provides new products through network platform and traditional industries, provide new value, new services, mining new business model; the development of the Internet can penetrate into all walks of life, can create infinite value, provide great convenience and creativity to people's life. With the development of the logistics industry, it has become the nuclear pillar of the national industry. In every logistics process, it needs the support of the Internet, and it has become a very precious asset of logistics enterprises. With the Internet and big data, it will help logistics enterprises to transform and upgrade in the direction of intelligent logistics, so that enterprises can quickly grasp the market environment and understand customer needs, so as to make correct and effective decisions. China is a big agricultural country and agriculture is the basic industry of national economic development. As an agricultural country, most agricultural logistics, circulation links and long circulation cycle, and the greatest economic benefit and the quality and safety of agricultural products. n order to solve this problem, this paper mainly by literature research, comparative analysis and network research methods, combined with logistics management knowledge, the introduction of intelligent logistics, agricultural products logistics integration theory, X province in 2015-2020 forestry animal husbandry fishery total output value and 2020 per capita disposable income (10186 yuan) data integration, in-depth research on the Internet brings opportunities and challenges for agricultural products logistics enterprises.","PeriodicalId":232563,"journal":{"name":"2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129222203","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