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检索条件"任意字段=12th International Conference on Computing and Pattern Recognition, ICCPR 2023"

共 284 条记录，以下是31-40 订阅

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Enhanced Face recognition Intelligent System on Smart Home Security and Control with CNN 12

Enhanced Face Recognition Intelligent System on Smart Home S...

引用

12th IEEE international conference on Communication, Networks and Satellite, COMNETSAT 2023

作者： Mandala, Satria Ramadhan, Rifqi Irsan, Muhamad Engineering School of Computing Bandung Indonesia Telkom University School of Computing Bandung Indonesia

ISBN: (纸本)9798350341102

In recent years, there has been a growing interest in research related to facial recognition and its integration into home security systems. However, the challenge of achieving high face detection accuracy remains unresolved. Many studies based on Convolutional Neural Networks (CNNs) have yielded only moderate results in face detection, and their real-time implementation remains a concern. To address these issues, this research proposes a solution by implementing three transfer learning methods: ResNeXt, GhostNet, and MobileNet V2. the aim is to enhance the accuracy of CNN-based face detection. Additionally, this study combines transfer learning-based facial detection with Internet of things (IoT) technology to improve home security. Experimental results demonstrate the impressive capability of the GhostNet algorithm, achieving an accuracy rate of 98.75% in face detection. Moreover, the recall, precision, and F1 score metrics stand at 98.73%, 98.78%, and 98.75%, respectively. these findings conclude that GhostNet is superior compared to the other two algorithms, i.e., ResNeXt and MobileNet V2. this research concludes that transfer learning offers a promising solution to overcome the accuracy challenges in face detection for home security. © 2023 IEEE.

关键词： Face recognition

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Distance Transform in Images and Connected Plane Graphs 12th

Distance Transform in Images and Connected Plane Graphs

引用

12th international conference on pattern recognition Applications and Methods (ICPRAM)

作者： Banaeyan, Majid Kropatsch, Walter G. TU Wien Pattern Recognit & Image Proc Grp Vienna Austria

ISBN: (纸本)9783031547256;9783031547263

the distance transform (DT) serves as a crucial operation in numerous image processing and pattern recognition methods, finding broad applications in areas such as skeletonization, map-matching robot self-localization, biomedical imaging, and analysis of binary images. the concept of DT computation can also be extended to non-grid structures and graphs for the calculation of the shortest paths within a graph. this paper introduces two distinct algorithms: the first calculates the DT within a connected plane graph, while the second is designed to compute the DT in a binary image. Both algorithms demonstrate parallel logarithmic complexity of O(log(n)), with n representing the maximum diameter of the largest region in either the connected plane graph or the binary image. To attain this level of complexity, we make the assumption that a sufficient number of independent processing elements are available to facilitate massively parallel processing. Both methods utilize the hierarchical irregular pyramid structure, thereby retaining topological information across regions. these algorithms operate entirely on a local level, making them conducive to parallel implementations. the GPU implementation of these algorithms showcases high performance, with memory bandwidth posing the only significant constraint. the logarithmic complexity of the algorithms boosts execution speed, making them particularly suited to handling large images.

关键词： Distance transform Connected plane graph Parallel logarithmic complexity Irregular graph pyramids Parallel processing

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Generalized Median Computation for Consensus Learning: A Brief Survey 20th

Generalized Median Computation for Consensus Learning: A Bri...

引用

20th international conference on Computer Analysis of Images and patterns (CAIP)

作者： Jiang, Xiaoyi Nienkoetter, Andreas Univ Munster Fac Math & Comp Sci Munster Germany Sichuan Univ Hongkong Polytech Univ Inst Disaster Management & Reconstruct Chengdu Sichuan Peoples R China

ISBN: (纸本)9783031442360;9783031442377

computing a consensus object from a set of given objects is a core problem in machine learning and pattern recognition. A popular approach is the formulation of generalized median as an optimization problem. the concept of generalized median has been studied for numerous problem domains with a broad range of applications. Currently, the research is widely scattered in the literature and no comprehensive survey is available. this brief survey contributes to closing this gap and systematically discusses the relevant issues of generalized median computation. In particular, we present a taxonomy of computation frameworks and methods. We also outline a number of future research directions.

关键词： pattern recognition

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Efficient Regression with Feature Selection Based on L12-Norm 4

Efficient Regression with Feature Selection Based on L12-Nor...

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4th IEEE international conference on pattern recognition and Machine Learning, PRML 2023

作者： Lei, Yu Li, Qin You, Jane Shenzhen Institute of Information Technology School of Software Engineering Shenzhen China Xidian University School of Telecommunications Engineering Xi'an China The Hong Kong Polytechnic University Department of Computing Hong Kong Hong Kong

ISBN: (纸本)9798350324303

Feature selection is one of the most important components of many machine learning applications. Most of the existing sparse coding-based methods only concerned with the regularization of the transformation matrix, but ignoring the sparsity of projected features in the intrinsic feature space. In this paper, we introduce a novel regularization with 12-norm, called class specificity distribution term. It aims to ensure that samples with the same label could obey a specific distribution, while data from the different categories should have different distributions in the intrinsic feature space. then we propose a novel embedded feature selection framework based on regression and class specificity distribution term measured by 12-norm, termed RL12. An efficient augmented Lagrange multipliers based optimization algorithm is proposed to solve the 12-norm regularization iteratively. Experimental results demonstrate the effectiveness of our method. © 2023 IEEE.

关键词： Feature Selection

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Edge AI patterns 12th

Edge AI Patterns

引用

12th international conference on AI and Mobile Services, AIMS 2023

作者： Shan, Richard Shan, Tony Computing Technology Solutions Inc. Charlotte United States Charlotte NC28277 United States

ISBN: (纸本)9783031451393

this paper comprehensively explores a spectrum of AI patterns tailored for edge computing, including regular, branched, circular, serial, concurrent, cascade, input fusion, hierarchical, and ensemble patterns. As edge devices grapple with limited resources and the need for real-time decision-making, these patterns offer structured methodologies for efficient data processing, adaptive decision-making, and enhanced accuracy. through in-depth analyses of each pattern’s characteristics, approaches, and implementations, the pattern model equips users with a systematic understanding of the diverse strategies available for orchestrating AI workflows in edge computing environments, paving the way for improved system design, scalability, and performance across a myriad of application domains. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Classification (of information)

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Comparative Study of pattern recognition Techniques in the Classification of Vertebral Column Diseases 12th

Comparative Study of Pattern Recognition Techniques in the...

引用

12th international Congress in Telematics and computing, WITCOM 2023

作者： Rojas-López, Alam Gabriel Uriarte-Arcia, Abril Valeria Rodríguez-Molina, Alejandro Villarreal-Cervantes, Miguel Gabriel Mechatronics Section Postgraduate Department OMD Laboratory Instituto Politécnico Nacional - Centro de Innovación y Desarrollo Tecnológico en Cómputo Mexico City07700 Mexico Research and Postgraduate Division Tecnológico Nacional de México/IT de Tlalnepantla Tlalnepantla de Baz54070 Mexico

ISBN: (纸本)9783031453151

this work compares popular classifiers based on pattern recognition techniques of supervised learning, including k-Nearest Neighbors, Naïve Bayes, Support Vector Machines, Artificial Neural Networks, and Decision Trees. Such techniques are applied to a dataset related to vertebral column orthopedic diseases. Different parameter values employed by each classifier are tested, resulting in an accuracy of around 80 % in almost all approaches, where the k-Nearest Neighbors alternatives were the most accurate. Finally, a brief discussion of particular highlights of how the metrics affect the performances of the classifiers is presented. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Decision trees

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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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SER-Fuse: An Emotion recognition Application Utilizing Multi-Modal, Multi-Lingual, and Multi-Feature Fusion 23

SER-Fuse: An Emotion Recognition Application Utilizing Multi...

引用

12th international Symposium on Information and Communication Technology, SOICT 2023

作者： Pham, Nhat Truong Phan, Le thi Dang, Duc Ngoc Minh Manavalan, Balachandran Dept. of Integrative Biotechnology Sungkyunkwan University Gyeonggi-do Suwon Korea Republic of Dept. of Computing Fundamental Fpt University Ho Chi Minh Viet Nam

ISBN: (纸本)9798400708916

Speech emotion recognition (SER) is a crucial aspect of affective computing and human-computer interaction, yet effectively identifying emotions in different speakers and languages remains challenging. this paper introduces SER-Fuse, a multi-modal SER application that is designed to address the complexities of multiple speakers and languages. Our approach leverages diverse audio/speech embeddings and text embeddings to extract optimal features for multi-modal SER. We subsequently employ multi-feature fusion to integrate embedding features across modalities and languages. Experimental results archived on the English-Chinese emotional speech (ECES) dataset reveal that SER-Fuse attains competitive performance in the multi-lingual approach compared to the single-lingual approaches. Furthermore, we provide the implementation of SER-Fuse for download at https://***/nhattruongpham/SER-Fuse to support reproducibility and local deployment. © 2023 ACM.

关键词： Modal analysis

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PLR-Based Heat Treatment Process State Identification Method 12

PLR-Based Heat Treatment Process State Identification Method

引用

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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13th international conference on Innovations in Bio-Inspired computing and Applications, IBICA 2022, and 12th World Congress on Information and Communication Technologies, WICT 2022

13th International Conference on Innovations in Bio-Inspired...

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13th international conference on Innovations in Bio-Inspired computing and Applications, IBICA 2022, and 12th World Congress on Information and Communication Technologies, WICT 2022

ISBN: (纸本)9783031274985

the proceedings contain 86 papers. the special focus in this conference is on Innovations in Bio-Inspired computing and Applications. the topics include: A Novel Approach to the Two-Dimensional Cargo Load Problem;vehicle Detection from Aerial Imagery Using Principal Component Analysis and Deep Learning;bio-inspired Heterogeneity in Swarm Robots;software Defect Prediction Using Cellular Automata as an Ensemble Strategy to Combine Classification Techniques;a Systematic Literature Review on Home Health Care Management;the Impact of the Size of the Partition in the Performance of Bat Algorithm;automatic Diagnosis Framework for Catheters and Tubes Semantic Segmentation and Placement Errors Detection;how Artificial Intelligence Can Revolutionize Software Testing Techniques;e-Assessment in Medical Education: From Paper to Platform;Evolution of Configuration Data in CGP Format Using Parallel GA on Embryonic Fabric;DeepPRS: A Deep Learning Integrated pattern recognition Methodology for Secure Data in Cloud Environment;Automated Depression Diagnosis in MDD (Major Depressive Disorder) Patients Using EEG Signal;an Effective Deep Learning Classification of Diabetes Based Eye Disease Grades: An Retinal Analysis Approach;extracting and Analyzing Terms with the Component ‘Green’ in the Bulgarian Language: A Big Data Approach;Apartments Waste Disposal Location Evaluation Using TOPSIS and Fuzzy TOPSIS Methods;detection of Cracks in Building Facades Using Infrared thermography;optimizing Pre-processing for Foetal Cardiac Ultra Sound Image Classification;a Review on Dimensionality Reduction for Machine Learning;detecting Depression on Social Platforms Using Machine Learning;impact of Green Hydrogen Production on Energy Pricing;Cross Synergetic Mobilenet-VGG16 for UML Multiclass Diagrams Classification;the Future in Fishfarms: An Ocean of Technologies to Explore;breast Cancer Identification Using Improved DarkNet53 Model;anomaly Detection Framework.

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