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

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6th International conference on Smart Computing and Informatics, SCI 2024

6th International Conference on Smart Computing and Informat...

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6th International conference on Smart Computing and Informatics, SCI 2024

ISBN: (纸本)9789819619801

The proceedings contain 46 papers. The special focus in this conference is on Smart Computing and Informatics. The topics include: Resilient Domain Authentication Framework for Enhancing Digital Identity Security;traffic Sign Detection with Pattern Recognition Techniques Using image processing;exploring Advanced Techniques in Natural Language processing and Machine Learning for In-depth Analysis of Insurance Claims;Network Intrusion Detection with SMOTE-ENN and Deep Learning Techniques;leveraging Transfer Learning to Enhance Location Accuracy in Mapping Services: A Case Study of Google Maps;assessment of Enhanced Email Spam Detection System Through Machine Learning algorithms;machine Learning Methods for Predicting Traffic Congestion Forecasting;hybridization of Computational Intelligence Algorithm for Scheduling of Tasks and Balancing of Load in Cloud Network;MDSV: Mobs Detection by Enhanced Fused Feature Base Deep Neural Network from Surveillance Camera;ioT-Based Solution for Enhanced Tracking of Individuals Living with Dementia;a Novel Task Scheduling Algorithm in Heterogeneous Multi-cloud Environment;Evaluating the Integration and Usage of AI in Higher Education;evaluating the Connectional Benefits of Artificial Intelligence in the Digital Classroom;Influence of AI as an Aspect of Modern Education Era in Present World;Hilbert–Huang Transform Framework-Based Email and SMS Spam Detection;the Advancement and Utilization of Artificial Intelligence and Machine Learning in the Financial Industry and Its Impact on Macro and Microeconomics;analysis on the Cutting-Edge Approach to Assess Artificial Intelligence’s Educational Consequences in Contemporary Studies;data Analytics in Sales and Marketing: A Comprehensive Methodology for Business Analysts;Wireless Energy Transfer for UAV (Drone) Using Machine Learning.

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Monitoring Method and Application of Icing Thickness and Icing Type of Distribution Network Overhead Line Based on A Hydrophobic Marker and image Defogging 2

Monitoring Method and Application of Icing Thickness and Ici...

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IEEE 2nd International conference on Power Science and Technology (ICPST)

作者： He, Xingping Yang, Jingsi Zeng, Hanye Li, Qingdong Liu, Chengcheng Zhou, Jiye Zhaotong Power Supply Bur Yunnan Power Grid Co Lt China Southern Power Grid Zhaotong Yunnan Peoples R China

ISBN: (纸本)9798350349047;9798350349030

This paper presents a monitoring method and application of icing thickness (ITs) and icing type (ITe) of distribution network overhead line (DNOL) based on a hydrophobic marker (HM) and image defogging (ID). Firstly, a HM tailored specifically for application in DNOL is devised;Subsequently, image processing (IP) techniques are employed to process the acquired images. These techniques include ID, Canny edge detection to identify edges, Imfill Operator for fill holes (or gaps) within binary images, and Bwperim Operator for precise edge extraction, the application of these operator collectively yields a clear and defined edge image. Finally, using the distinct characteristics of various ITe within the RGB color space and utilizing algorithms, the ITe and ITs are accurately calculated. Consequently, relevant information pertaining to line icing of DNOL is obtained, enhancing the accuracy and reliability of line icing monitoring. This, in turn, bolsters the safety and stability of the power system. The results of this study are anticipated to establish a solid theoretical and practical foundation for icing monitoring on DNOL. Furthermore, they are expected to offer substantial support for ensuring the safe and stable operation of power systems, thereby enhancing their overall resilience and reliability.

关键词： distribution network overhead line hydrophobic marker image defogging icing thickness icing type

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Auto-Detection of Handwritten Text Documents using Improved image processing Technique 15

Auto-Detection of Handwritten Text Documents using Improved ...

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15th International conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Srinivasan, M. Radha, K. Priya, V. Basha, Shaik Mahaboob Ravi, S. Bannari Amman Institute of Technology Department of Eee Sathyamangalam India Dr.Mahalingam College of Engineering and Technology Department of Cse Coimbatore Pollachi India Department of Microbiology TamilNadu Chennai India School of Engineering Department of Ece Andhra Pradesh Tirupati India Saveetha University Saveetha School of Engineering Department of Vlsi Microelectronics Chennai India

ISBN: (纸本)9798350370249

Automobile detection of handwritten text files is vital in document control systems. It includes the process of automatically figuring out and extracting handwritten text from pictures and converting it into editable virtual text. This method is challenging due to the variations in handwriting styles and the complexity of handwritten textual content reputation. Current methods for auto-detection depend upon conventional picture processing strategies, including thresholding, segmentation, and characteristic extraction, which need to be more robust to handle various handwriting patterns. A stepped-forward photograph processing method for automobile detection of handwritten textual content documents is proposed to deal with this issue. The technique uses deep mastering algorithms, including convolutional neural networks (CNNs), to robotically research the features of handwritten textual content and classify it appropriately. The proposed technique additionally employs facts augmentation techniques to boost the dataset's variety, making it more robust for variations in handwriting styles. Experimental consequences on an extensive handwritten textual content file dataset show that the proposed technique outperforms traditional techniques, accomplishing a better accuracy fee. The advantages of this method encompass its adaptability to one-of-a-kind handwriting styles, its velocity, and its potential to deal with handwritten textual content in numerous languages © 2024 IEEE.

关键词： Appropriately Augmentation Consequences Experimental Handwritten Mastering

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Plant Disease Detection by means of K-Means Clustering and HSV Algorithm

Plant Disease Detection by means of K-Means Clustering and H...

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2023 International conference on Sustainable Computing and Smart systems, ICSCSS 2023

作者： Anirudh Reddy, R. Sai Prasanna, K. Mani Teja, B. Deepak Reddy, N. Pranay Sai Reddy, N. Shiva, N. B v Raju Institute of Technology Department of Ece TelanganaMedak Dt Narsapur India

ISBN: (纸本)9798350333602

The productivity of agriculture determines the economy of a country. To boost agricultural productivity and improve product quality, plant diseases must be identified. It is seen that the agricultural production is rapidly growing and various techniques are being used for it. One of the emerging technologies is fogponics. In this technology, plants are grown using fog which is directly exposed to roots instead of water. This methodology has a limitation of being infected with diseases due to a lack of nutrition. Plant leaf patterns can be observed visually to diagnose disease using traditional methods;however, they require the use of human resources. image classification is a technique to detect the diseases of plants that are already trained to model. If the disease is detected, then acknowledgment has been sent to the user that the plant is affected by the disease. This dataset must be uploaded to carry out the software implementation, and specific operations must be carried out on it to obtain the findings, namely whether the disease is detected. Regarding real-time applications, any model (Raspberry Pi) is used to hold substantial amounts of data. Devoid of any datasets for model training, a few different techniques are applied to identify anomalous leaf conditions. A color feature of the leaf area is used in image-processing algorithms to detect plant infections and diseases. © 2023 IEEE.

关键词： image classification

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Development of a Procedure for Improving the Effectiveness of Personal Identification systems Based on the Analysis of Facial images 17

Development of a Procedure for Improving the Effectiveness o...

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17th International Scientific and Technical conference on Dynamics of systems, Mechanisms and Machines, Dynamics 2023

作者： Tatarkanov, A.A. Umyskov, A.A. Kuklin, V. Zh. Institute of Design and Technology Informatics of RAS Moscow Russia

ISBN: (纸本)9798350358315

This research aims to develop a new procedure to improve the performance of the personal identification system. This process will be based on the analysis of digital facial images using special artificial intelligence technologies. Additionally, it is emphasized that the successful development of a completely new neural network algorithm for personality identification and its special robust modification are required to achieve this goal. Furthermore, it is essential that this algorithm demonstrates increased effectiveness in identifying faces. As part of this algorithm, two key components are distinguished, namely, an algorithm aimed at determining the area where a face is located in an image, which involves the use of a standard version of a convolutional neural network. And the presented neural network algorithm is the second component, which is designed for personal identification with a specific robust modification. The studies presented have shown that an algorithm with a proposed architecture, will have around 25 times less weight parameters than the algorithms utilized at present. Also, unlike other algorithms, it was possible to improve the level of accuracy. © 2023 IEEE.

关键词： image enhancement

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HisDataTJ: imageJ Plugin for Global Thresholding with Application in Bread Porosity Evaluation 3

HisDataTJ: ImageJ Plugin for Global Thresholding with Applic...

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3rd International conference on Communications, Information, Electronic and Energy systems, CIEES 2022

作者： Bosakova-Ardenska, A.D. Danev, A. Gogova, T. University of Food Technologies Dept. of Computer Systems And Technologies Plovdiv Bulgaria University of Food Technologies Dept. of Technology of Cereals Fodder Bread And Confectionery Products Plovdiv Bulgaria

ISBN: (数字)9781665491495

ISBN: (纸本)9781665491495

It is developed a plugin for imageJ that performs global thresholding through four innovative thresholding algorithms, which are designed last five years. These algorithms are HisMedian, SubMedian-1, SubMedian-2, and HisAnalysis. The algorithm SubMedian-2 uses secondary median value in the sub-histogram as a threshold and it is applied for white bread porosity evaluation. The algorithm HisAnalysis uses as a threshold a color with maximal frequency in image histogram and it is applied for brown bread porosity evaluation. It is implemented also an algorithm (MedHASM-2) that combines methods for threshold finding which are used by HisAnalysis and SubMedian-2 algorithms. This paper presents a research of possibilities for application of global thresholding algorithms in wheat bread type "Dobrudzha"porosity evaluation. Four samples of different brands of wheat bread are used for experiments. The porosity of tested samples is measured through physicochemical analysis. The results are compared with results of image processing through correlation analysis. The highest correlation coefficients are calculated for results of thresholding with algorithms HisAnalysis and MedHASM-2. Based on the results of statistical data processing it is proposed an equation for calculation of the bread porosity using the ratio of white pixels to all in binary images. The average error for bread porosity calculated with the proposed equation is about 1% using the algorithm MedHASM-2 and about 3% using the algorithm HisAnalysis. © 2022 IEEE.

关键词： Porosity

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Development of UAV image processing algorithms for Early Detection of Fires in Natural Ecosystems

Development of UAV Image Processing Algorithms for Early Det...

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IEEE International conference on Actual Problems of Unmanned Air Vehicles Developments Proceedings (APUAVD)

作者： Volodymyr Hnatushenko Tetiana Bulana Bohdan Molodets Daniil Boldyriev Information Technologies & Computer Engineering Department Dnipro University of Technology Dnipro Ukraine

ISBN: (数字)9798331534141

ISBN: (纸本)9798331534158

The article discusses image processing algorithms for creating a full-fledged fire detection system based on UAV collections. The wildfire detection issue is solved using artificial intelligence: YOLOv8 model. The fire classification based on the fuel map obtained using LiDAR data was also implemented. The scheme of the information system that will perform detection and classification is proposed. This information system is useful at the decision-making stage to determine the strategy and tactics of firefighting. With several improvements, the system can be used to process incoming data in real time.

关键词： Wildfires Laser radar image processing Ecosystems Autonomous aerial vehicles Real-time systems Classification algorithms Fuels Monitoring Information systems

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Research on Traditional Art image Reconstruction Method Based on Computer vision Analysis

Research on Traditional Art Image Reconstruction Method Base...

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Artificial Intelligence and Autonomous Robot systems (AIARS), International conference on

作者： Xunmiao Ruan Guangdong University of Science &Technology Dongguan Guangdong China

ISBN: (数字)9798350376173

ISBN: (纸本)9798350376180

In the information age, image processing technology has become prevalent across various domains. To enhance image correction, computer vision algorithms can be employed. Traditional methods for structural system identification rely on wired or wireless measurement systems for data gathering, which can be cumbersome and time-consuming due to the need for arranging sensors and data collection equipment. The proposed system involves two primary steps: line drawing extraction and rendering. During the extraction phase, an edge detection technique that integrates low and middle-level visual information is utilized. Based on the results of traditional edge detection, the edges are simplified and connected using computer vision principles. This approach treats image processing as the focal point and aims to establish a scientific model for distorted images. image restoration can be facilitated through sample image filtering and noise reduction techniques. Additionally, this article delves into the principles and associated technologies of computer vision, analyzing patterns of visual interaction. Chinese traditional art imagery, as a cultural medium and symbol, fulfills an artistic communication function while preserving the nation's rich cultural heritage. The image processing techniques grounded in computer vision algorithms offer numerous advantages and superior accuracy.

关键词： Computer vision visualization Art Machine learning algorithms image edge detection Distortion Real-time systems Global communication Cultural differences image reconstruction

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Dynamic Scene Representation for Docking in Urban Waters Using a Stereo Camera 6

Dynamic Scene Representation for Docking in Urban Waters Usi...

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International Maritime and Port Technology and Development conference (MTEC) / 6th International conference on Maritime Autonomous Surface Ships (ICMASS)

作者： Nygard, Trym Anthonsen Brekke, Edmund Forland Mester, Rudolf Stahl, Annette Norwegian Univ Sci & Technol NTNU Dept Engn Cybernet Trondheim Norway Norwegian Univ Sci & Technol NTNU Dept Comp Sci Trondheim Norway

To navigate and dock safely in urban waters, an autonomous ferry must assess its safe navigation paths by identifying navigable free space and potential obstacles. A deep understanding of its surroundings is crucial for situational awareness. Knowing which objects are static and dynamic is an indispensable ingredient for path planning algorithms and collision avoidance systems, and is especially useful for docking operations, as moving obstacles can interfere with the optimal path to the dock. To handle all types of obstacles, we present a novel dynamic scene representation for docking in urban waters using a short baseline stereo camera. Obstacles protruding from the water surface are represented with vertically oriented rectangles, known as stixels. The stixels are tracked over consecutive frames with dense optical flow. Together with stereo correspondences, their 3D motion is estimated. Stixels representing the same object are grouped together into line segments which are classified as either dynamic or static based on the motion of its associated stixels. Our dynamic representation presents objects in the 3D camera coordinate system as a bird's eye view map. Additionally, stereo depth uncertainty can significantly impact depth estimates and is considered using a Kalman filter, providing smooth position and velocity estimates. We test our dynamic scene representation on a real docking scenario recorded with an autonomous ferry using a stereo camera. We evaluate the accuracy of the reconstructed 3D scene points and the velocity estimates of the dynamic objects using LiDAR and GNSS.

关键词： Stereo image processing

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algorithms for image processing of Micro-Objects of Medical Diagnostics systems

Algorithms for Image Processing of Micro-Objects of Medical ...

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International Russian Smart Industry conference (SmartIndustryCon)

作者： Isroil I. Jumanov Rustam A. Safarov Department of “Artifical intellegence and information systems” Samarkand State University named after Sharof Rashidov Samarkand Uzbekistan Department of Control Theory and Information Security Samarkand State University named after Sharof Rashidov Samarkand Uzbekistan

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

Constructive approaches, principles, models for optimizing the identification of micro-objects based on the use of statistical, dynamic models with mechanisms for filtering noise, foreign particles on images of medical objects and pollen grains have been developed. Methods for optimizing the identification of micro-objects with the selection of characteristic objects in the image, the combination of image models with the mechanisms of segmentation, filtering, transformation, and alignment of the laser image processing zone with the CAD model are proposed. algorithms for selecting the contours of objects on an image using a border detector in the transverse direction to each vector of the CAD model have been developed. Modeling of images of microsamples for medical diagnostics of chest diseases was carried out. The width, straightness of the boundaries of structural objects, local defects, parameters of regulation and synchronization of the components of the vision system are determined. algorithms for image processing under conditions of a priori insufficiency, uncertainty of parameters, and low accuracy of data processing are studied. A mechanism for suppressing impulse noise and noise is implemented based on various filtering methods, preserving the boundaries of objects and small-sized parts. Mathematical expressions for estimating identification errors due to non-stationarity, inadequacy of approximation, interpolation, extrapolation of the image contourare obtained, which are synthesized with cubic, biquadratic, interpolation spline functions and wavelet transforms. A software package for recognition and classification of micro-objects has been developed.

关键词： Solid modeling Interpolation image segmentation Filtering Measurement by laser beam Laser modes Vectors Object recognition Synchronization Medical diagnosis

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