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

共 12594 条记录，以下是181-190 订阅

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A Vision-Based System for Real-Time Monitoring of Water Quality in Natural and Artificial Reservoirs

A Vision-Based System for Real-Time Monitoring of Water Qual...

引用

Intelligent Data Communication Technologies and Internet of Things (IDCIoT), International conference on

作者： Shripad Bhatlawande Shrihari Mohole Yash Pahade Swati Shilaskar Aditya Munjale Vishwakarma Institute of technology Pune India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

Manual sampling and laboratory testing are the mainstays of traditional water quality monitoring methods, which causes delays in data processing and decision-making. This study proposes an enhanced monitoring of water quality system that uses machine learning algorithms to classify and segment water samples in real-time, thereby overcoming these restrictions. Water samples are classified as “Clean” or “Polluted” having an accuracy of 83.99% using a CNN model. The CNN model, trained over 20 epochs, effectively learns patterns from the dataset to deliver precise results. Additionally, a U-Net model is implemented for image segmentation, generating masks that accurately highlight areas of interest within the water samples, with a segmentation accuracy of 68%. Streamlit's intuitive interface makes it simple for users to upload images and get immediate feedback on water quality. This system helps to improve the health of the environment monitoring with automating the method of water quality evaluation. It does this by providing a simpler, quicker, and scalable solution that enables prompt, data-driven actions.

关键词： image segmentation Accuracy Water quality Manuals Streaming media User interfaces Reservoirs Water pollution Real-time systems Testing

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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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An Intelligent Lane, Object Detection and Speed Estimation for Ego-Vehicles using Perception algorithms

An Intelligent Lane, Object Detection and Speed Estimation f...

引用

International Symposium on Advanced Computing and Communication (ISACC)

作者： Kukkamudi Sunidhi J. N.V.R. Swarup Kumar Gorla Srinivas Cetty Yamini Dept. of CSE GST GITAM Deemed to be University India

ISBN: (数字)9798331523893

ISBN: (纸本)9798331523909

Autonomous vehicles promise to revolutionize transportation by expanding mobility and improving traffic safety. All of this future auto tech hinges on autonomous vehicle perception - the processing of visual input to vital Advanced Driving Assistance functions such as lane detection, vehicle and pedestrian recognition, and traffic sign detection. The goal of this work is to increase the level of autonomy in ego vehicles, which can drive through challenging traffic situations (completely autonomously). This research will then take on one of the portions with a low latency and high accuracy target, which is safety + efficiency (using ADAS – Advanced Driver Assistance systems). The system proposes an ego vehicle-based computer vision solution for pedestrian, vehicle, and traffic sign detection along with lane detection. The entire system consists of many small systems like the YOLO-NAS Module, Gaussian Blur Module, Hough line transform, and Canny Edge Detection. A detailed flow diagram is given at the end and is curated during the experiment analysis meeting.

关键词： YOLO Pedestrians Accuracy Lane detection image edge detection Estimation Transforms Real-time systems Safety Autonomous vehicles

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

2nd International Conference on Information Technologies and...

引用

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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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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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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Research on image processing and Recognition algorithms in Software Information systems Based on Deep Learning 3

Research on Image Processing and Recognition Algorithms in S...

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3rd IEEE International conference on Electrical Engineering, Big Data and algorithms, EEBDA 2024

作者： Tang, Xiaojun Radio and Television Monitoring Center of Shandong Province Shandong Jinan China

ISBN: (纸本)9798350380989

With the rapid development of deep learning technology, its application in image processing and recognition has become a hot research topic. The application of these technologies in software information systems such as automatic image classification, facial recognition, and medical image analysis not only improves processing efficiency but also enhances recognition accuracy. This article focuses on the training and deployment of adversarial generative network models in deep learning algorithms for graphic processing and recognition applications. Finally, two sets of simulation experiments were conducted, and the results are as follows: in the face recognition system, the recognition accuracy optimized by the deep learning algorithm based on adversarial generative networks improved by an average of 8.9% compared to traditional methods. In the traffic sign recognition system, the overall average recall index improved by 12.45%. This article proposes an improved network architecture and training strategy, which significantly improves the quality of image generation and the accuracy of recognition models in software information systems. © 2024 IEEE.

关键词： deep learning image processing image recognition software information systems

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