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检索条件"任意字段=Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition"

共 696 条记录，以下是311-320 订阅

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Enhancing Safety and Independence: A Smart Switch Solution for Elderly Individuals Living Independently 12

Enhancing Safety and Independence: A Smart Switch Solution f...

引用

12th international conference on System Modeling and Advancement in Research Trends, SMART 2023

作者： Babu, Prakash Ahmad, Nazia Hussain, Sajithunisa George, Remya P. Shukla, Ravi Shankar Jain, Vishal Acharya Institute of Technology Dept of It Bangalore India The Applied College Imam Abdulrahman Bin Faisal University Computer Science Department Saudi Arabia College of Computing and Informatics Saudi Electronic University Department of Computer Science Saudi Arabia Sharda University India

ISBN: (纸本)9798350369861

As the world's population ages, more and more people will need assistance with daily tasks, such as making sure their homes are safe and secure for themselves and their loved ones. this study presents a new smart switch technology that aims to make houses safer, more independent, and more comfortable for older people. the smart switch uses the Internet of things (IoT) and an intuitive user interface to make it easy for the elderly to control their household appliances, which in turn reduces the likelihood of accidents and allows caregivers to remotely monitor their well-being. this switch has been meticulously designed to meet the unique physical and cognitive requirements of older users by actively involving those users in the design process. Initial research shows that users' home environment management skills significantly increase, which has a favorable effect on their everyday lives and overall health. By improving the lives of elderly people who live independently, the study does double duty: it advances smart home technology and meets a pressing social need. © 2023 IEEE.

关键词： Domestic appliances

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A Quality Control Model for Lung Cancer Based on A Standardized Treatment Mode 12

A Quality Control Model for Lung Cancer Based on A Standardi...

引用

12th international conference of Information and Communication Technology, ICTech 2023

作者： Dong, LiYing Wang, Ning Zhao, Kui Ma, Ming Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang110168 China University of Chinese Academy of Sciences Beijing100049 China General Hospital of Northern Theater Command Shenyang China

ISBN: (纸本)9798350332919

In the medical field, quality of care is one of the most important goals, and only by achieving good quality of care can we provide better health services to the society. therefore, it is particularly important to implement quality control of the diagnosis and treatment process. In this paper, we propose a lung cancer quality control model based on the standardized judgment of the treatment model to address the requirements of lung cancer treatment quality control, the complex content of medical text data, and the irregular recording time. First, the word vector is trained by BERT pre-training model;then, the K-medoids algorithm is used to mine the standardized treatment patterns, and the time-aware LSTM unit is used to deal with the uneven input interval on this basis;finally, the attention mechanism is introduced to highlight the different contributions of the visit days to complete the prediction of the next cycle of lung cancer treatment items. the experimental results showed that the recall and average accuracy of the BERT-TLSTM-ATT fusion model reached 0.895 and 0.782, respectively, which performed well compared with other models and effectively controlled the quality of next-cycle treatment, achieving the goal of quality control of all aspects of lung cancer treatment. © 2023 IEEE.

关键词： Quality control

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SAFD: A Statistical Analysis-Based Feature Point Descriptor 12

SAFD: A Statistical Analysis-Based Feature Point Descriptor

引用

12th international conference of Information and Communication Technology, ICTech 2023

作者： Zheng, Liaomo Han, Yuhu Zhang, Qiongwei Li, Lunxing Shenyang Casnc Technology Co. Ltd Shenyang China Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350332919

Describing and matching feature points is one of the most basic tasks in many computer vision tasks. For example, in tasks such as structure from motion, simultaneous localization and mapping, and image stitching, the quality of feature point matching directly determines the accuracy of the vision task, which in turn affects the availability of specific applications such as VR, MR, autonomous driving, and robot navigation. the current mainstream feature point method has the problem that the number of mismatches is relatively large, which will cause a lot of interference to computer vision tasks based on feature point matching. Traditional feature point descriptors only use the feature point and very little information in its neighborhood, so mismatches are prone to occur. the main contribution of this paper is to propose a feature point descriptor and a corresponding matching method. the core idea is to use multiple dimensions of information to describe a feature point, and then integrate the differences in each dimension to evaluate the similarity between the two feature points, and then improve the matching rate of feature points. the experimental results show that the feature description and matching algorithm proposed in this paper is superior to the popular ORB algorithm in terms of matching rate. © 2023 IEEE.

关键词： Computer vision

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Inversion and Prediction of Carbon Emissions Based on Remote Sensing Data and BP-XGBoost Model 12

Inversion and Prediction of Carbon Emissions Based on Remote...

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12th international conference of Information and Communication Technology, ICTech 2023

作者： Wang, Guodong Wang, Ning Zhou, Xiaolei Qiu, Yan Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China The Open University of Deyang Deyang China

ISBN: (纸本)9798350332919

In this paper, we first use the BP model optimized by particle swarm optimization (PSO) to integrate DMSP-OLS nighttime light data and NPP-VIIRS nighttime light data to establish a long-time series of nighttime light data sets were obtained. And using the integrated nighttime light data, temperature data and geographical data, based on the Bayesian optimization algorithm (BO) optimized XGBoost model, a carbon dioxide emission prediction model was constructed. In this study, the dataset based on nighttime light data shows a significant positive correlation to carbon emissions. As a result, the dataset can be used to estimate carbon emissions. And when using the BO-XGBoost model to invert carbon emissions, the R2 is 0.9791, and the RMSE is 29.9118, which is the most accurate predictive outcome compared to other models. the results of this study will help simplify the work of carbon emission accounting and provide an important basis for regional carbon emission policies. © 2023 IEEE.

关键词： Forecasting

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Water Quality Prediction Based on CEEMDAN-LSTM-LINREG Model 12

Water Quality Prediction Based on CEEMDAN-LSTM-LINREG Model

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12th international conference of Information and Communication Technology, ICTech 2023

作者： Zhang, Peng Zhou, XiaoLei Liu, ShouZheng Dou, ZhiQiang Shenyang Institute of Computing Technology University of Chinese Academy of Sciences Shenyang China Liaoning Environmental Monitoring Association Shenyang China Shenyang Ecological Environment Monitoring Center of Liaoning Province Shenyang China

ISBN: (纸本)9798350332919

In this paper, CEEMDAN is introduced to perform modal decomposition of indicator data to capture the characteristics of the data at different time scales. Each feature is constructed as a stacked LSTM sub-prediction model. Since different features represent different dimensions, the cumulative sum of the results of each sub-model as the final prediction result will lead to the problem of error superposition. In this paper, a linear regression model is introduced to self-learn the corresponding weights of each sub-model, and the weighted sum method is used to fuse the results of each sub-model to alleviate the error superposition problem. the dissolved oxygen, ammonia nitrogen, PH and permanganate indicators are taken as examples to verify the prediction model proposed in this paper. the experimental results show that in the models constructed by CEEMDAN and EMD decomposition algorithms, the prediction accuracy of each index is improved by 11.88%, 4.38%, 1.33%, 3.38 and 19.29%, 3.65%, 0.61 %, 2.65% respectively after introducing the linear regression model. It shows that the combined model constructed in this paper has strong generalization ability and robustness. © 2023 IEEE.

关键词： Water quality

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Information, Communication and computing Technology 1

引用

丛书名： Communications in Computer and Information Science

1000年

作者： Jemal Abawajy João Manuel R.S. Tavares Latika Kharb Deepak Chahal Ali Bou Nassif

ISBN: (数字)9783031438387

ISBN: (纸本)9783031438370

this book constitutes the refereed proceedings of the 8th international conference on Information, Communication and computing Technology, ICICCT 2023, held in New Delhi, India, during May 27, 2023.;the 14 full papers included in this book were carefully reviewed and selected from 60 submissions. they were organized in topical sections as follows: global platform for researchers, scientists and practitioners from both academia and industry to present their research and development activities in all the aspects of pattern recognition and computational Intelligence techniques.

关键词： Computer Systems Organization and Communication Networks Artificial Intelligence Computer Communication Networks Data Mining and Knowledge Discovery Computer Imaging, Vision, pattern recognition and Graphics

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A Review of Deep Learning Solutions in 360° Video Streaming 12

A Review of Deep Learning Solutions in 360° Video Streaming

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12th international conference on Modern Circuits and Systems Technologies, MOCAST 2023

作者： Mahmoud, Moatasim Rizou, Stamatia Panayides, Andreas S. Lazaridis, Pavlos I. Kantartzis, Nikolaos V. Karagiannidis, George K. Zaharis, Zaharias D. Singular Logic European Projects Department Athens14564 Greece VIDEOMICS Group CYENS Centre of Excellence Nicosia Cyprus University of Huddersfield School of Computing and Engineering HuddersfieldHD1 3DH United Kingdom Aristotle University of Thessaloniki School of Electrical and Computer Engineering Thessaloniki54124 Greece

ISBN: (纸本)9798350321074

the spread of virtual reality and 360° video applications has raised research interest in developing new streaming techniques. On one hand, 360° videos rely on strict network requirements compared to conventional 2D videos. Realizing an adequate user experience is subject to ultra-low latency and huge bitrate requirements. On the other hand, 360° videos have distinct characteristics that allow for innovative streaming solutions. these solutions have benefited from the advancements in deep learning for optimizing the transmission under restricted network resources. In this paper, we review existing works employing deep learning in 360° video transmission and we highlight the challenges associated with 360° video streaming. © 2023 IEEE.

关键词： Augmented reality

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Scalable parallel processing design for real time handwritten OCR

Scalable parallel processing design for real time handwritte...

引用

international conference on pattern recognition

作者： A. Cuhadar A.C. Downton Electronic Systems Engineering Department University of Essex Colchester UK

this paper presents a generalised technique for parallelising embedded computer vision and pattern recognition applications and shows how it has been applied to the recognition of handwritten postcodes on envelopes. the technique is based upon the utilisation of pipelines of processor farms (PPF), and is applicable to any embedded system with continuous input/output data streams. the postcode recogniser combines temporal multiplexing and data parallelism to achieve a speedup of 21.4 compared with the original sequential application, using a total of 52 transputers.

关键词： Parallel processing Process design Optical character recognition software Pipelines Dictionaries Handwriting recognition Concurrent computing throughput Systems engineering and theory Computer vision

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Ant Colony Optimization for Resource Allocation in Cloud computing Environments 12

Ant Colony Optimization for Resource Allocation in Cloud Com...

引用

12th IEEE international conference on Intelligent Data Acquisition and Advanced computing Systems: Technology and Applications, IDAACS 2023

作者： Kniazhyk, Taras Muliarevych, Oleksandr Lviv Polytechnic National University Lviv79013 Ukraine

ISBN: (纸本)9798350358056

this article delves into cloud computing technologies, addressing the challenges and concerns that arise in this domain, specifically focusing on resource allocation. We investigate and compare three optimization algorithms - Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Genetic Algorithm (GA) - in the context of their applications, objectives, and mechanisms of action. Additionally, the article highlights the significance of each algorithm in optimizing cloud resources and discusses their advantages and drawbacks. For cloud computing with higher complexity, it becomes increasingly important to develop efficient strategies for managing and allocating resources, which in turn helps organizations control costs and improve performance. Prepared comparative analysis aims to provide a comprehensive understanding of the three algorithms, equipping decision-makers with the knowledge to select the most suitable optimization method for their specific cloud computing needs and challenges. © 2023 IEEE.

关键词： ACo cloud computing Ga Psa resource allocation

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Mining progressive confident rules 06

Mining progressive confident rules

引用

KDD 2006: 12th ACM SIGKDD international conference on Knowledge Discovery and Data Mining

作者： Zhang, Minghua Hsu, Wynne Lee, Mong Li School of Computing National University of Singapore Singapore 117543 Singapore

ISBN: (纸本)1595933395

Many real world objects have states that change over time. By tracking the state sequences of these objects, we can study their behavior and take preventive measures before they reach some undesirable states. In this paper, we propose a new kind of pattern called progressive confident rules to describe sequences of states with an increasing confidence that lead to a particular end state. We give a formal definition of progressive confident rules and their concise set. We devise pruning strategies to reduce the enormous search space. Experiment result shows that the proposed algorithm is efficient and scalable. We also demonstrate the application of progressive confident rules in classification. Copyright 2006 ACM.

关键词： Data mining

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