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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems III"

共 14633 条记录，以下是201-210 订阅

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Edge-IoT Architecture-Based Visualization Service Platform for RTO Real-Time Monitoring

Edge-IoT Architecture-Based Visualization Service Platform f...

引用

International conference on Advanced Communication Technology (ICACT)

作者： Hoon-Min Park Dal-Hwan Yoon Hyun-Min Jung Dae-Hee Lee Tae-Yeung Lim Hyun Kim Myung-Ki Jang Emsolution Co. Ltd Suwon Korea Department of Electronic Engineering Semyung University Korea Devicenet Co. Ltd Korea

ISBN: (数字)9791188428137

ISBN: (纸本)9798331507602

In this study, we present the Edge IoT Architecture (Architecture) for analyzing the real-time state information of the regenerative thermal oxidizer (RTO) and implement a visualization method. The Edge-IoT architecture system interfaces with the programmable logic control (PLC) that controls the monitoring of RTO operations and transmits real-time data to a remote server, analyzes the channel data received through the IoT to build a database, and visualizes the characteristics of database (DB) analysis. IoT architecture implementation for fault diagnosis and maintenance of RTO designs IoT circuits on PLC control panels that control monitoring. Compatibility and information security are considered to facilitate remote maintenance. The received data is segmented by each channel and analyzed by a visualization algorithm to detect anomalies in the segmented data. At this time, the visualized data is judged to be normal, insufficient, or warning, depending on the threshold.

关键词： image edge detection Data visualization Signal processing algorithms Signal processing Real-time systems Maintenance Thermal analysis Visual databases Servers Monitoring

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Bone Fracture Detection using CNN and VGG

Bone Fracture Detection using CNN and VGG

引用

Ambient Intelligence in Health Care (ICAIHC), International conference on

作者： Kasvi Soni Aanya Gupta Karishma Dhyani Sunil Kumar Department of IoT and IS Manipal University Jaipur Jaipur India

ISBN: (数字)9798331530259

ISBN: (纸本)9798331530266

Technology has played a huge role in human evolution since time immemorial. Now it is not only limited to engineers and data scientists, but far beyond, to even medicine. With increasing load on medical professionals and healthcare systems, digitalization can come handy. The traditional X-ray imaging gives unclear images of bone components in tissue making it difficult for surgeons to diagnose. Using technology, accurate diagnosis can be achieved. This includes a series of steps comprising pre-processing, edge detection, feature extraction and machine learning classifications. Machine learning algorithms such as Convolutional Neural Networks(CNN) and Visual Geometry Group(VGG) were used on a dataset consisting of 9246 training, 506 test and 829 validation images with 0.95 and 0.85 accuracies respectively. The data loss for CNN was found to be 0.24 in comparison to 0.4 for VGG. So from statistical inference, CNN is better.

关键词： Visualization Accuracy image edge detection Medical services Machine learning Feature extraction Bones Convolutional neural networks Medical diagnostic imaging X-ray imaging

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2nd International conference on Information Technologies and Their Applications, ITTA 2024

2nd International Conference on Information Technologies and...

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2nd International conference on Information Technologies and Their Applications, ITTA 2024

ISBN: (纸本)9783031734168

The proceedings contain 60 papers. The special focus in this conference is on Information Technologies and Their Applications. The topics include: Turkish Legal Single-Document Summarizing;technologies and systems for Monitoring the Onset of Accidents at Strategic Construction;optimizing Feature Distributions for Unsupervised Deep Learning-Based Fabric Defect Detection and Localization;conservation of Wildlife in Hunting Tourism Using Artificial Intelligence and image processing in Smart Firearms;optimizing Microarray Gene Selection in Colon Cancer: An Enhanced Metaheuristic Algorithm for Feature Selection;securing Vehicular Ad-Hoc Networks: A Blockchain and Software Defined Network Approach for Enhanced Efficiency, Safety, and Security;influence of Process Noise Biases to Satellite Attitude Filters’ Estimates;information-Retrieval System of Rock Pictures of Different Countries and Continents;convergence of Sharpness-Aware Minimization with Momentum;vulnerability Assessment and Penetration Testing of University Network;preliminary Orbit Estimation for Turksat 5B via Extended and Unscented Kalman Filtering;Three-Axis Attitude Determination of a Nanosatellite Using Optimized TRIAD algorithms;computer System of Evaluation of the Mass Exam Results Based on Recognition of Handprinted Azerbaijani Characters;Empirical Analysis of Conformer Impact on the CTC-CRF Model in Kazakh Speech Recognition;ontological Approach to Describing the Interaction of Information Processes in Intelligent systems;LANet: Lightweight Attention Network for Medical image Segmentation;Lightweight Hybrid CNN Model for Face Presentation Attack Detection;disaggregation Analyses of the External/Internal Parameters for Chloride Diffusion in Concrete Structures: Artificial Intelligence by k-means Algorithm;k-means for Small Earthquakes. Alternative Disaggregation Analyses by Considering Wave Components and Soil Types;algorithm for Distributing Incoming Messages Among Handlers.

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1st International conference on Advances in Artificial Intelligence and Machine Learning in Big Data processing, AAIMB 2023

1st International Conference on Advances in Artificial Intel...

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1st International conference on Advances in Artificial Intelligence and Machine Learning in Big Data processing, AAIMB 2023

ISBN: (纸本)9783031730641

The proceedings contain 51 papers. The special focus in this conference is on Advances in Artificial Intelligence and Machine Learning in Big Data processing. The topics include: Topological Navigation of Path Planning Using a Hybrid Architecture in Wheeled Mobile Robot;abnormal Behaviour Detection in Surveillance Videos;ISAApp – image Based Smart Attendance Application;a Self-learning Ai-Based Information Leak Protection System;enhancing Abnormal Object Detection in Camera-Based systems Through Computer Vision and Deep Learning Techniques;Detection and Classification of Brain Tumor in Magnetic Resonance images Using CNN;diagnosis of Parkinson’s Disease Using Machine Learning and Deep Learning Techniques;a Survey on Deep Learning Based Human Activity Recognition System;a Deep Learning Approach for Non - invasive Body Mass Index Calculation;Early-Stage Detection of Alzheimer’s Disease Using MRI Scans with Deep Learning;penguin Search Optimization with Deep Learning Based Cybersecurity Malware Spectrogram image Classification;Detection and Classification of Skin Disease Using CNN;estimation of Above Ground Biomass Using Machine Learning and Deep Learning algorithms: A Review;URL Phishing Detection Using Deep Learning and Machine Learning Techniques;enhanced Disease Recognition and Classification in Black Gram Plant Leaves Using Deep Learning;Ensemble Deep Learning Approach for Identification of DDOS Attack;ROCLT: Enhanced Text Classifier for Sentiment on Imbalanced Multiclass Tweet Data Using Hybrid Deep Learning Techniques;computer Vision to Animal Footprint Classification Based on Deep Learning Model;Speech Emotion Recognition Using CNN Classifier Based on Deep Learning Model;face Detection and Recognition for Criminal Identification System Using Deep Learning.

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1st International conference on Advances in Artificial Intelligence and Machine Learning in Big Data processing, AAIMB 2023

1st International Conference on Advances in Artificial Intel...

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1st International conference on Advances in Artificial Intelligence and Machine Learning in Big Data processing, AAIMB 2023

ISBN: (纸本)9783031730672

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2nd International conference on Information Technologies and Their Applications, ITTA 2024

2nd International Conference on Information Technologies and...

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2nd International conference on Information Technologies and Their Applications, ITTA 2024

ISBN: (纸本)9783031734199

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NEURAHOLO: A System for High-Resolution 3D Human Digitization on Holograms 2nd

NEURAHOLO: A System for High-Resolution 3D Human Digitizatio...

引用

2nd International conference on Intelligent systems and Data Science, ISDS 2024

作者： Nguyen, Hoang Pham Ngoc, Thai Anh Huynh Le Gia, Luat Le Gia, Khoi College of Information and Communication Technology- Can Tho University Can Tho Viet Nam

ISBN: (纸本)9789819796151

Amid the growing prominence of Holographic Projection technology in Vietnam’s technology trend, we introduce NEURAHOLO: an innovative system designed to convert 2D images into 3D models for holographic displays. The system compares two advanced image processing algorithms for background removal U2-net and Mediapipe Selfie Segmentation followed by PIFuHD for 3D model generation, and a 3D Led Holodisplay for visualization. Our evaluation on the Supervisely Person Dataset with over 1000 images resulted in an IoU score of 0.9309 for U2-net, outperforming Mediapipe Selfie Segmentation, which scored 0.8467. The Chamfer Distance was used to measure the accuracy of the 3D models, with an average error of just 0.986, thereby corroborating the system’s adeptness at precise 3D model re-creation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： image segmentation

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Multi-Partner Project: Architectures and Design Methodologies to Accelerate AI Workloads. The ICSC Flagship 2 Project

Multi-Partner Project: Architectures and Design Methodologie...

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Design, Automation and Test in Europe conference and Exhibition

作者： Cristina Silvano Fabrizio Ferrandi Serena Curzel Daniele Ielmini Stefania Perri Fanny Spagnolo Pasquale Corsonello Sebastiano Fabio Schifano Cristian Zambelli Angelo Garofalo Francesco Conti Luca Benini Politecnico di Milano Milano Italy Università della Calabria Rende CS Italy Università degli Studi di Ferrara Ferrara Italy Università di Bologna Bologna Italy

ISBN: (数字)9783982674100

ISBN: (纸本)9798331534646

Recent pre-exascale and exascale supercomputers have driven the development of increasingly sophisticated AI models for diverse applications, including image recognition and classification, natural language processing, and generative AI. These applications require specialized hardware accelerators, to handle the heavy computational demands of AI algorithms in an energy-efficient manner. Today, AI accelerators are deployed across various systems, from low-power edge devices to large-scale servers, high-performance computing (HPC) infrastructures, and data centers. The primary objective of the ICSC Flagship 2 project, discussed in this paper, is to develop heterogeneous hardware platforms optimized to accelerate HPC and big data applications. Specifically, this paper provides an overview of the key challenges addressed and the achievements realized at the current intermediate stage of the ICSC Flagship 2 project focused on architectures, technologies, and design methodologies to design efficient hardware accelerators for AI workloads, such as deep learning (DL) and transformer models.

关键词： Design methodology High performance computing Memory architecture AI accelerators Transformers Energy efficiency Supercomputers Natural language processing Servers Hardware acceleration

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Improving the Construction of a Multi-modal Underwater image Recognition System for Anomaly Detection in Nuclear Power Plant Cooling Source Areas 8th

Improving the Construction of a Multi-modal Underwater Image...

引用

8th International conference on Life System Modeling and Simulation, LSMS 2024 and 8th International conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Huang, Yu Wang, Kai Gu, Yuntao Zhou, Chaofan Guo, Yuanjun Yang, Zhile China Nuclear Industry Maintenance Co. Ltd. Shenzhen Branch Shenzhen China Taiyuan University of Technology Taiyuan030024 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

ISBN: (纸本)9789819602315

The cooling facilities of nuclear power plants are crucial components for transferring the accumulated heat from the reactor to the external environment. However, the complex structure of these facilities makes traditional manual anomaly detection methods inefficient, time-consuming, and poses certain risks to human safety. Therefore, this paper proposes a system for anomaly detection in the cooling source areas of nuclear power plants based on improved multi-modal underwater image recognition. The system utilizes deep learning and image processing techniques to denoise, compensate for illumination, and correct water flow in collected images of the cooling source areas. Wavelet-based noise removal techniques are applied to further enhance image clarity, providing accurate inputs for machine vision algorithms. By training an improved convolutional neural network model, real-time automatic identification and classification of underwater anomalies such as foreign objects and pipeline cracks are achieved, significantly improving the monitoring efficiency and safety of the cooling source areas in nuclear power plants. Comparative analysis with actual cases validates the excellent stability and accuracy of the proposed method in handling underwater operation images in the cooling source areas of nuclear power plants. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Nuclear power plants

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ISAApp – image Based Smart Attendance Application 1st

ISAApp – Image Based Smart Attendance Application

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1st International conference on Advances in Artificial Intelligence and Machine Learning in Big Data processing, AAIMB 2023

作者： Dutta, Aritra Suseela, G. Niranjana, G. Boral, Pushpita Gupta, Pranav Pal, Subha Bal Department of Networking and Communications School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur603203 India

ISBN: (纸本)9783031730641

This research paper introduces a Python-based implementation of a facial recognition system utilizing face recognition and Open CV libraries. The system has diverse applications, including security, surveillance, social media, and entertainment. By employing a pre-trained neural network, the system enables users to select an image file and accurately detect and recognize faces within it. Additionally, it includes functionality to encode faces from a specified folder, enabling comparison against the faces in the target image. By employing a blend of face detection, feature extraction, and machine learning algorithms, the system effectively identifies, and labels faces in images. Its effectiveness illustrates the potential of facial recognition technology for numerous applications, while also underscoring the ethical and privacy concerns associated with such technology. Addressing these issues and developing more precise and dependable systems would require further research. The primary objective of the system is to offer an improved solution for classroom attendance, ensuring the avoidance of false attendance records and significantly reducing the time required for attendance taking, through the application of machine learning solutions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Support vector machines

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