Advances in computer, signals and systems最新文献_第5页

Research on the Progress of Autonomous Technology in Robot Assisted Surgery 机器人辅助手术自主技术进展研究

Advances in computer, signals and systems Pub Date : 2023-01-01 DOI: 10.23977/acss.2023.070704

引用次数: 0

Research on video target tracking algorithm based on deep neural network 基于深度神经网络的视频目标跟踪算法研究

Advances in computer, signals and systems Pub Date : 2023-01-01 DOI: 10.23977/acss.2023.070809

{"title":"Research on video target tracking algorithm based on deep neural network","authors":"","doi":"10.23977/acss.2023.070809","DOIUrl":"https://doi.org/10.23977/acss.2023.070809","url":null,"abstract":": In the field of computer vision applications, visual object tracking is a widely researched and hot-topic area, finding extensive practical applications in many key visual domains and demonstrating promising real-world performance. However, due to various factors such as lighting variations, scale changes, background clutter, low resolution, and other interferences, visual object tracking requires improvements on multiple fronts. In this paper, a video object tracking algorithm based on deep neural networks is proposed while ensuring real-time tracking. Addressing the limitation of traditional visual object tracking algorithms based on correlation filtering theory, which rely on shallow handcrafted features, this algorithm first leverages a deep neural network model to extract deep features of the target to be tracked. Given that different convolutional layers encode different information in their deep feature representations, these distinct layer features are subsequently fused to enhance representation capability. Furthermore, a kernel correlation-based approach is employed to boost the tracking speed of the visual object tracking algorithm. The experimental results demonstrate that the method proposed in this paper achieves a balance between target tracking accuracy and speed, enhancing the robustness of visual object tracking algorithms in complex and noisy backgrounds.","PeriodicalId":495216,"journal":{"name":"Advances in computer, signals and systems","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135009502","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

Model Predictive Control of Hydrogen Pressure of Multi-Stack Fuel Cell System 多堆燃料电池系统氢压力的模型预测控制

Advances in computer, signals and systems Pub Date : 2023-01-01 DOI: 10.23977/acss.2023.070902

引用次数: 0

Automatic Bag-breaking Classification and Collection System for Kitchen Waste Based on OpenCV 基于OpenCV的餐厨垃圾自动破袋分类收集系统

Advances in computer, signals and systems Pub Date : 2023-01-01 DOI: 10.23977/acss.2023.070713

{"title":"Automatic Bag-breaking Classification and Collection System for Kitchen Waste Based on OpenCV","authors":"","doi":"10.23977/acss.2023.070713","DOIUrl":"https://doi.org/10.23977/acss.2023.070713","url":null,"abstract":"Traditional kitchen waste disposal requires manual separation of plastic bags from food waste, which is cumbersome and unhygienic. However, the capacity, shape, and size of the plastic bags used to hold kitchen waste are different, resulting in an unstable bottom position of the plastic bags when putting them in. Therefore, it is difficult to break plastic bags of any size by using traditional mechanical devices. This paper introduces a computer vision-based automatic bag-breaking classification and collection system for kitchen waste, which aims to solve various pain points in the process of food waste classification and placement. The system involves computer vision, single-chip microcomputer, and internet of things (IoT) technology. When residents dispose of kitchen waste, they only need to hang the bag on the device, the system will visually judge the size and position of the plastic bag, and then control the motor to adjust the plastic bag to the corresponding position to break the bag, and the kitchen waste will fall into the kitchen waste in the garbage bin, it is judged by visual inspection whether the bag breaking is completed, and if it is completed, the plastic bag is thrown into another garbage bin.","PeriodicalId":495216,"journal":{"name":"Advances in computer, signals and systems","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135498081","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 navigation interface design of children's health application based on AHP-entropy weight method 基于ahp -熵权法的儿童健康应用导航界面设计研究

Advances in computer, signals and systems Pub Date : 2023-01-01 DOI: 10.23977/acss.2023.070706

引用次数: 0

Research on NLP Based Automatic Summarization Generation Method for Medical Texts 基于自然语言处理的医学文本自动摘要生成方法研究

Advances in computer, signals and systems Pub Date : 2023-01-01 DOI: 10.23977/acss.2023.070903

{"title":"Research on NLP Based Automatic Summarization Generation Method for Medical Texts","authors":"","doi":"10.23977/acss.2023.070903","DOIUrl":"https://doi.org/10.23977/acss.2023.070903","url":null,"abstract":"The fundamental concept underpinning text summarization technology revolves around the capacity to encapsulate the original information into a succinct form, thus equipping individuals to promptly extract essential content from vast data repositories and liberating users from the cumbersome task of processing extensive textual material. In recent years, the exponential proliferation of data in biomedical literature, patient case records, and healthcare documentation, has presented a pressing challenge. This research undertakes the integration of Natural Language Processing (NLP)-related technologies into the domain of medical text summarization. It puts forth a novel solution for generative automatic summarization, with a specific focus on enhancing the model's proficiency in assimilating the semantic nuances inherent in biomedical texts. The methodology incorporates within existing text summarization frameworks to optimize the model's efficacy in handling biomedical data. The empirical findings presented in this study attest to the remarkable precision of the sentence similarity calculation method introduced herein. In a comparative analysis against four alternative methodologies, this approach achieves a high accuracy rate of 90.6%. This outcome highlights the superior predictive performance of the sentence integration similarity calculation method proposed in this research.","PeriodicalId":495216,"journal":{"name":"Advances in computer, signals and systems","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135446844","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

A Modular Home Automation System Based on IoT Technology 基于物联网技术的模块化家庭自动化系统

Advances in computer, signals and systems Pub Date : 2023-01-01 DOI: 10.23977/acss.2023.070807

引用次数: 0

Research on Semantic Analysis-Based Recognition of Telecommunication Fraud Discourse Patterns 基于语义分析的电信欺诈语篇模式识别研究

Advances in computer, signals and systems Pub Date : 2023-01-01 DOI: 10.23977/acss.2023.070808

引用次数: 0