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

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Automated Machine Learning Evaluation of Squat Movement patterns Using Smartphone and CoreML 12

Automated Machine Learning Evaluation of Squat Movement Patt...

引用

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

作者： Sokolowska, Marta Podpora, Michal Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics Opole45-758 Poland

ISBN: (纸本)9798350358056

there is a vast diversity of Machine Learning use cases, and both the hardware and the methodology itself are constantly getting better. this article presents a very specific use case - the recognising, classifying, and evaluation of human physical activity by using just a video stream from a smartphone and potentially instructing people how to exercise to get better results. the paper presents two key aspects of the challenge: (1) defining the problem in the physical activity domain and choosing a proper ML approach and tool, and (2) conducting the experiment using consumer-grade hardware (a smartphone) to evaluate if the proposed methodology is applicable using an easy-to-use tool and widely accessible hardware for users with limited (or without) Machine Learning experience. Chapter II presents the process of gathering and preparing the dataset, while the next chapter presents the creation of a Machine Learning model, model training using the acquired dataset, and the model performance. It was possible to obtain the result of 92.4% validation accuracy for the squat movement pattern classification model. the trained model can be used in an ML smartphone application for evaluation of user-provided examples of squats. © 2023 IEEE.

关键词： action classiication Artiicial Intelligence Machine Learning movement patterns pattern recognition video analysis

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CNN-based Smart Waste Management System in Fog computing Environment 12

CNN-based Smart Waste Management System in Fog Computing Env...

引用

12th IEEE international conference on Communication Systems and Network Technologies, CSNT 2023

作者： Kaur, Mandeep Aron, Rajni Wadhwa, Heena Oo, Htet Ne Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Mpstme Nmims University Mumbai India

ISBN: (纸本)9781665462617

Data processing occurs on the central server in cloud computing. Data transfers from the node to the cloud take a long time. Fog computing has therefore been presented as a solution to these problems. the fog computing nodes handles data processing on network end only. On the other hand, if it requires further processing, it is sent to the central server to complete the task. the processing time is cut down, and the data is more effectively used. In geologically separated places where connectivity may be uneven, fog is generally beneficial. It has become more common in recent years to use ML to enhance fog computing applications and provide fog services, including efficient resource management, security, lowering latency and energy consumption, and traffic modelling. this article proposes a machine learning approach for smart waste management application of fog computing. the proposed approach is based on CNN approach that classifies provided data into different categories that can be used in future for processing waste management data. the proposed approach provides 95.83% accuracy. © 2023 IEEE.

关键词： Fog

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Multi-Spill Surface Target Tracking Based on Oil Particle-Random Point pattern 12

Multi-Spill Surface Target Tracking Based on Oil Particle-Ra...

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12th IEEE international conference on Control, Automation and Information Sciences, ICCAIS 2023

作者： Sun, Qiankun Liu, Weifeng Wen, Chenglin Shaanxi University of Science and Technology School of Electrical and Control Engineering Xi'an China Guangdong University of Petrochemical Technology School of Automation Maoming China

ISBN: (纸本)9798350328783

In complex marine environments, it is difficult to obtain important parameters such as the number, location, and shape of oil spill surfaces;multiple oil spill surfaces may overlap and merge, which makes the accurate tracking of multiple oil spill surfaces even more difficult. To address the aforementioned issues, proposed a multi-spill surface target tracking method based on the oil particle-random point pattern. Firstly, the oil spill surface is represented by an oil particle model. then, a random point pattern algorithm is introduced to cluster the oil spill surface. Finally, the GLMB filtering method is utilized to track the centroid trajectory of the oil spill surface, and its shape and concentration information is recorded at the same time. Simulation experiments show the effectiveness of the proposed algorithm. © 2023 IEEE.

关键词： Oil spills

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Deep web repeated pattern discovering based on the largest block strategy

Deep web repeated pattern discovering based on the largest b...

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2012 IEEE 12th international conference on Computer and Information Technology, CIT 2012

作者： Ye, Feiyue Tang, Haibo Luo, Xiangfeng School of Computer Engineering and Science Shanghai Univercity Shanghai China

ISBN: (纸本)9780769548586

Repeated pattern is a common phenomenon in query result pages of deep web sites. the deep web back-end data can be accessed by mining repeated patterns. So far, most of the algorithms of discovering repeated pattern use traditional web information extraction methods. But the recall percentage and accuracy are not high. How to obtain the repeated pattern accurately and completely is still a difficulty. We propose a method based on the largest block strategy to discover such pattern. the core of the method is using the largest block strategy to discover the repeated pattern layer. We can quickly navigate to the region of the entity data, and then analyze the sub tree in this area, finally, get the simplified repeated pattern of the deep web site. According to the results of the experiment, this method can get the repeated pattern data more accurately and more completely than the traditional methods. It can also address the multi-pattern problem which has not been solved yet in other methods. © 2012 IEEE.

关键词： Websites

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proceedings - 12th IEEE international conference on Computational Science and Engineering, CSE 2009

Proceedings - 12th IEEE International Conference on Computat...

引用

2009 international conference on Computational Science and Engineering, CSE '09

ISBN: (纸本)9780769538235

the proceedings contain 65 papers. the topics discussed include: performance modeling and analysis of integrated WLANs and internet-access mesh networks;a trade-off approach to optimal resource allocation algorithm with cache technology in ubiquitous computing environment;self-tuning the parameter of adaptive non-linear sampling method for flow statistics;a cognitive approach to achieve fair uplink and downlink utilities in wireless networks;a weighted-dissimilarity-based anomaly detection method for mobile wireless networks;a novel resource management scheme for integrated multiple traffic heterogeneous systems;scalable APRIORI-based frequent pattern discovery;event-driven approach for logic-based complex event processing;incremental discovery of sequential patterns using a backward mining approach;and data distribution methods for communication localization in multi-clusters with heterogeneous network.

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Analytic outlier removal in line fitting 12

Analytic outlier removal in line fitting

引用

12th IAPR international conference on pattern recognition - conference B: pattern recognition and Neural Networks, ICPR 1994

作者： Netanyahu, Nathan S. Weiss, Isaac Space Data and Computing Division NASA Goddard Space and Flight Center GreenbeltMD20771 United States Center for Automation Research University of Maryland College ParkMD20742 United States

ISBN: (纸本)0818662700

the conventional ordinary least squares (OLS) method of fitting a. line to a set of data points is notoriously unreliable when the amount of random noise in the input (such as an image) is significant compared with the amount of data that is correlated with the line itself. Although points which lie far away from the line (i.e., outliers) are usually only to noise, they contribute the most to the squared distances, thereby skewing the line estimate from its correct position. In this paper we present an analytic method of separating the data of interest from the outliers. We assume that the overall data (i.e., the line data plus the noise) can be modeled as a mixture of two statistical distributions. Applying a variant of the method of moments (MoM) to the assumed model yields an analytic estimate of the desired line. Key words: Line fitting, outliers, noise removal, mixture models, method of moments. © 1994 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Method of moments

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Mean AR-Local Binary pattern For Facial Expressions Classification Based on KNN Classifier 10

Mean AR-Local Binary Pattern For Facial Expressions Classifi...

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17th INDIACom;2023 10th international conference on computing for Sustainable Global Development, INDIACom 2023

作者： Srilatha, Narubonia Reddy, Lokeswara Computer Science and Engineering Jntua Ananthapur India Computer Science and Engineering Kadapa India

ISBN: (纸本)9789380544472

According to its significance, facial expression recognition (FER) has reached an incredibly prominent position in the field of image processing, beginning in the 1990s and continuing to the present day. Face recognition, feature extraction, and face categorization are the three common steps in FER. In contrast to the various FER systems described for recognizing just part of face expressions, the system presented in this study can identify all eight fundamental facial emotions (neutral, pleased, angry, contempt, surprise, sad, fear, and disgust). We employ the Japanese Female Facial Expression (JAFFE) and the Extended Cohn-Kanade (CK+) datasets to verify our results. the presented methods LBP patterns in this work namely, Asymmetric Region LBP(AR-LBP), Mean Asymmetric Region LBP (Mean AR-LBP), We used GLCM feature extractor technique for feature selection. For the given input image, the GLCM calculates different features factors named Contrast, Correlation, and Homogeneity, Entropy, Mean, variance, and dissimilarity which were results to a feature vector. the findings of the given approach, which employed K-Nearest Neighbor (KNN) to categories facial emotions, are then contrasted with those of the standard LBP pattern. the recognition rate utilizing the provided technique is 96% for the CK + data set and 97% for the JAFFE data set, as shown by the testing results. © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Emotion recognition

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Computation pattern driven reuse of manual optimizations for GPGPUs

Computation pattern driven reuse of manual optimizations for...

引用

2011 12th international conference on Parallel and Distributed computing, Applications and Technologies, PDCAT 2011

作者： Xu, Shixiong Han, Dongni Chen, Li Key Laboratory of Computer System and Architecture Institute of Computing Technology University of Chinese Beijing China

ISBN: (纸本)9780769545646

the wide application of General Purpose Graphic Processing Units (GPGPUs) results in large manual efforts on porting and optimizing algorithms on them. However, most existing automatic ways of generating GPGPU code fail to conduct optimization strategies regarding a specific computation and to reuse constantly evolving manual optimizations. In this paper, we present a computation pattern driven approach for computation-specific GPGPU code generation and optimization, which in turn reuses manual optimizations to a certain extent. We suggest language extensions to OpenMP, high-level data structure attributes, in order to assist the process of computation pattern matching and to help give users intuitive performance tuning parameters in the view of data structure attributes. We illustrate the feasibility of this approach through three important computation dwarfs, which are dense matrix, sparse matrix, and structured mesh computation in scientific computing. We also build a prototype OpenMP-to-CUDA translator that consists of computation pattern recognition and code template instantiation. the experimental results demonstrate the performance benefits of computation pattern driven method. To our best knowledge, it is the first work on reusing manual optimizations for GPGPUs with computation pattern driven approach. © 2011 IEEE.

关键词： Data structures

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PLR-Based Heat Treatment Process State Identification Method 12

PLR-Based Heat Treatment Process State Identification Method

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

作者： Li, YanXin Hu, Yi Tao, Zeng Zhao, YanQing Zhang, JunLong Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang110168 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9798350332919

In industrial production, the heat treatment process has a variety of forms, but the most basic process is the thermal process, it includes heating, insulation and cooling three stages. According to the importance of temperature and data characteristics in heat treatment industry, the pretreatment operation of data from dimensionality reduction, interpolation, normalization and feature representation of time series data were studied, and a method of temperature state recognition of heat treatment process based on piecewise linear representation was proposed. In this method, the change point of temperature data sequences was extracted by the deviation degree change between temperature data, and the initial temperature data was divided into trend segments based on this method. then, the trend segments were merged by the top-down algorithm to obtain the overall trend feature representation of the original data. According to the statistical characteristics of the data, the classifier is trained with RNN characteristics, and the processing state of the heat treatment process is finally obtained. Based on the actual temperature data of a heat treatment unit, experiments were carried out to verify the feasibility and effectiveness of the method. © 2023 IEEE.

关键词： Time series

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Construction of Sensitive Image Datasets Based on Generative Methods 12

Construction of Sensitive Image Datasets Based on Generative...

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

作者： Liu, Chang Zhang, Jie Yu, Bihui Wei, Jingxuan Chen, Xiaowei Yang, Hongxin Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Shenyang110168 China College of Information Liaoning University Shenyang110031 China

ISBN: (纸本)9798350332919

Due to the special nature of sensitive information, available sensitive data resources are relatively scarce to meet the needs of research in this field. the purpose of this paper is to construct a large sensitive image dataset by generative methods, with a view to supporting research exploration in related aspects. To achieve this goal, we adopt a new idea. First, we crawl sensitive and non-sensitive class datasets from web pages and filter them manually. Here, the sensitive classes mainly involve violence, terror and pornography;second, the selected data are used as the training set to fine-tune the pre-trained generative model;then, the fine-tuned generative model is used for sensitive/non-sensitive image generation, which expands the training dataset;finally, the generated training set is passed into the classification model to do the classification task for result verification. the experimental results show that the classification results of the expanded dataset using the generative method are higher than those of the original dataset, which proves the effectiveness of the generative method to construct the dataset. © 2023 IEEE.

关键词： Sensitive data

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