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28th International conference on image processing, Computer Vision, and Pattern Recognition, IPCV 2024, and 23rd International conference on Information and Knowledge Engineering, IKE 2024, held as part of the World Congress in Computer Science, Computer Engineering and Applied Computing, CSCE 2024

28th International Conference on Image Processing, Computer ...

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28th International conference on image processing, Computer Vision, and Pattern Recognition, IPCV 2024, and 23rd International conference on Information and Knowledge Engineering, IKE 2024, held as part of the World Congress in Computer Science, Computer Engineering and Applied Computing, CSCE 2024

ISBN: (纸本)9783031859328

The proceedings contain 28 papers. The special focus in this conference is on image processing, Computer Vision, and Pattern Recognition. The topics include: image-Based Seal Recognition: Approaches and Challenges in Current Automated systems;Deep Learning Techniques for Lunar Impact Crater Identification Based on CCD and DEM Data;silicon Wafer Map Defect Classification Using Artificial Intelligence Models;low Light image Enhancement Using Autoencoder-Based Deep Neural Networks;towards Elephants Intelligent Monitoring in Zakouma National Park, Chad;a Review of Multi-modal and Multi-view Applications in Hand-Drawn Sketch images;residential Real Estate image Classification for Property Valuation;Novel Method to Investigate Decay in Rotting Bananas Using RGB Color images;lalitha: A Hand Gesture-Based Computer Control System;dishari: A Novel Gesture-Based Educational Application for Specially Challenged People;mobility Anomaly Detection with Intelligent Video Surveillance;Weakly-Supervised Video Anomaly Detection Using Modified Anomaly Score Module and Modified BERT;Contour Detection of Seeds Based on Traditional and Convolutional Neural Network (CNN) Based algorithms;Early Detection of Lameness in Dairy Cattle Using Activity Data, image Analysis, AI and ML - An Approach for Improved Animal Welfare and Economic Impact;implications for Designing Hawks Detection with Data Augmentation and Network Optimizations;a Review of Detecting and Quantification of Cracks Using Convolutional Neural Networks and image processing Techniques;using Linkage Context for Automated Correction in Unsupervised Entity Resolution;the Rising Threat Against Modern Technology in Cybersecurity;an Online Bookstore Design and Implementation;cybersecurity: Sight and Foresight;the Application of Blockchain Technology in the Transmission of Semiconductor Process Recipes;the Use of Social Media and the Internet for the Facilitation of Human Trafficking.

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Fλ/d as a predictor of image classification algorithm performance

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APPLIED OPTICS 2025年第4期64卷 845-854页

作者： Hixson, Jonathan g. Teaney, Brian Finch, Michael f. Nehmetallah, George Driggers, Ronald US Army Combat Capabil Dev Command DEVCOM C5ISR Ctr RTI Aberdeen Proving Ground NY 21005 USA Catholic Univ Amer EECS Dept 620 Michigan Ave NE Washington DC 20064 USA Univ Arizona Wyant Coll Opt Sci Infrared Syst Grp Tucson AZ 85721 USA

This research studied the effect of variations in a sensor's F lambda/d metric value (FLD) on the performance of machine learning algorithms such as the YOLO (You Only Look Once) algorithm for object classification. The YOLO_v3 and YOLO_v10 algorithms were trained using static imagery provided in the commonly available training dataset provided by Teledyne FLIR systems. image processing techniques were used to degrade image quality of the test dataset also provided by Teledyne FLIR systems, simulating detector-limited to optics-limited performance, which results in a variation of the FLD metric between 0.339 and 7.98. The degraded test set was used to evaluate the performance of YOLO_v3 and YOLO_v10 for object classification and relate the FLD metric to the probability of detection. Results of YOLO_v3 and YOLO_v10 are presented for the varying levels of image degradation. A summary of the results is discussed along with recommendations for evaluating an algorithm's performance using a sensor's FLD metric value. (c) 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： image quality image sensors Imaging systems Imaging techniques Machine learning Sensor performance

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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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Quantum Variational Singular Value Decomposition: A new hybrid approach towards quantum image compression 17

Quantum Variational Singular Value Decomposition: A new hybr...

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17th International conference on COMmunication systems and NETworkS, COMSNETS 2025

作者： Britant Tiwari, Abhishek CDAC Uttar Pradesh Noida India

ISBN: (纸本)9798331531195

This research paper explores the application of singular value decomposition (SVD) in quantum image processing (QIP), specifically focusing on the computation of eigenvalues using variational quantum algorithms. SVD is a powerful mathematical tool in image processing, used for tasks such as image compression, noise reduction, and feature extraction. In this study, we propose quantum variational singular value decomposition (QVSVD) based on the variational quantum deflation (VQD) algorithm to determine the eigenvalues that contributes in calculating the singular values of the image matrix and eventually doing the SVD. This facilitates the extraction of eigenvalues with exponential speedup on real hardware compared to classical methods. We detail the implementation of this quantum algorithm within the framework of QIP, highlighting its advantages in terms of computational efficiency and accuracy on a Fault-Tolerant Quantum Computing (FTQC). Furthermore, we present a comparative analysis of the quantum and the classical method of SVD, demonstrating the accuracy of the image data. The simulation results validate the theoretical advantages of using quantum algorithms for SVD in image processing. This work not only underscores the potential of quantum computing in enhancing image processing techniques but also sets the stage for future research in the field, exploring more complex image processing tasks and other quantum algorithms. Our findings suggest that quantum image processing can offer unprecedented capabilities, paving the way for advancements in various applications such as medical imaging, remote sensing, and multimedia processing. © 2025 IEEE.

关键词： Noise abatement

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Application of Various Novel Computer image processing (CIP) algorithms in Digital Media Art images

Application of Various Novel Computer Image Processing (CIP)...

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2025 International conference on Multi-Agent systems for Collaborative Intelligence, ICMSCI 2025

作者： Du, Xian Shanghai Institute of Visual Arts Shanghai201620 China

ISBN: (纸本)9798331509828

With the continuous development of digital image processing algorithms, its application scenarios have been integrated from the simple research of a single image and a single algorithm to a multi-algorithm fusion analysis paradigm. Therefore, this study proposes a digital media art image analysis framework that combines multiple computer image processing (CIP) algorithms. This breakthrough covers three core architectures: image edge extraction, image style transfer, and image compression. In the image edge extraction module, this study designed an improved edge detection algorithm based on de-noising auto-encoder. This algorithm improves the accuracy of edge detection through multi-directional feature extraction and (I, O)-fuzzy rough set optimization, while maintaining global stability. In the image style transfer module, this study proposed a dual-module network. The network includes a texture translation network and a perceptual loss network, and achieves cross-domain style transfer through a fusion model. At the same time, the algorithm optimizes the perceptual loss function to enhance semantic matching capabilities. In the image compression module, this study uses chaotic systems to construct an optimized measurement matrix. Specifically, through a distributed data parallel training framework, a compression method based on the LPAC gradient sparse algorithm is constructed. By testing the three modules separately, the experimental results confirm the effectiveness of the proposed algorithm. © 2025 IEEE.

关键词： image compression

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A Comprehensive Survey of Methods for Identifying Counterfeit Banknotes Using image processing and Machine Learning 6th

A Comprehensive Survey of Methods for Identifying Counterfei...

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6th International conference on Intelligent Communication, Control and Devices, ICICCD 2024

作者： Sharmila, B. Sowmiya, A. Mary, Teena Sandeep, J. Sreeja, C.S. CHRIST University Dharmaram College Post Hosur Road Karnataka Bengaluru560029 India

ISBN: (纸本)9789819783281

The world economy is threatened by counterfeit currencies. Counterfeit currencies are often difficult, time-consuming and ineffective to identify manually. Automated methods based on image processing techniques and machine learning algorithms are helpful in detecting counterfeit notes. This survey paper reviews the current strategies on fake banknote detection using image processing techniques and machine learning algorithms. We discuss various stages of the detection process, including image acquisition, preprocessing, feature extraction and classification. Furthermore, we analyze the limitations and comparative performance of different algorithms and approaches mentioned in the literature. The survey aims to provide insights into the various methodologies, challenges and future directions in the field of fake banknote detection, facilitating the development of more robust and effective counterfeit detection systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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2009 16th International conference on systems, Signals and image processing, IWSSIP 2009

2009 16th International Conference on Systems, Signals and I...

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2009 16th International conference on systems, Signals and image processing, IWSSIP 2009

ISBN: (纸本)9781424445301

The proceedings contain 118 papers. The topics discussed include: a 90nm Manchester code generator with CMOS switches running at 2.4GHz and 5GHz;a comparative study to evaluate a text-independent speaker identification engine for Arabic speakers using a CHMM-based approach;a complete system for vehicle license plate recognition;a distributed intrusion detection system for ad-hoc wireless sensor networks: the AWISSENET distributed intrusion detection system;A FAST algorithm for adaptive filtering;a modular logic approach for P2P networks: a deductive object oriented framework for P2P networks;a new low-cost HF RFID loop antenna concept for metallic environments;a preliminary attempt to create a unified model for obtaining and processing geodata: geodata information sharing;a quantitative evaluation of privacy in location based services;and a simulation tool for RFID anti-collision algorithms based on ALOHA.

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Realization of Digital Protection Algorithm of National Traditional Culture Based on Virtual Reality Technology

Realization of Digital Protection Algorithm of National Trad...

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2024 International conference on Mechatronics and Intelligent Control, ICMIC 2024

作者： Chen, Hongxia Hou, Lanbao School of Literature and Media Jingchu University of Technology Jingmen448000 China School of Mathematics and Physics Jingchu University of Technology Jingmen448000 China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

National traditional culture and traditional technology are the products of historical precipitation and indispensable precious resources. The establishment of national cultural database is of great significance for the protection and inheritance of cultural heritage. Aiming at the specific functional requirements of traditional cultural digital protection system for image segmentation and retrieval, this paper focuses on the common algorithms of image segmentation and feature matching. This paper analyzes and compares the applicability and processing effect of each algorithm in ethnic patterns. EGBIS image segmentation algorithm and shape context feature matching algorithm are used to achieve high precision image processing. This paper designs and implements a national culture retrieval system that meets the application needs. Combined with the image characteristics of ethnic patterns and the application requirements of the system, this paper defines the concepts of source images, primitives and hyperprimitives, and establishes a relational database based on them. This study has laid a certain theoretical foundation for the study of digital inheritance of national culture. © 2025 SPIE.

关键词： image segmentation image retrieval Databases Feature extraction image processing algorithms and systems image processing Visualization Distance measurement Virtual reality Visual analytics

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Medical image Segmentation Techniques: Advances and Challenges 6

Medical Image Segmentation Techniques: Advances and Challeng...

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6th IEEE International conference on image processing, Applications and systems, IPAS 2025

作者： Boulehmi, Hela Filali, Rania Linda DGET ISET de Bizerte Bizerte Tunisia

ISBN: (纸本)9798331506520

Medical image segmentation plays a pivotal role in computer-aided diagnosis by facilitating the extraction of essential features necessary for disease detection and treatment strategies. The continuous progress in image processing technologies has led to the development of numerous segmentation methods, encompassing traditional algorithms, machine learning (ML)-driven approaches, and cutting-edge deep learning (DL) techniques. This study undertakes a comparative evaluation of these methods, focusing on their efficiency, accuracy, and suitability across different medical imaging modalities. It also delves into prominent segmentation techniques like thresholding, region-based methods, edge detection, graph cuts, active contour models, and convolutional neural networks (CNNs). Additionally, the paper explores ongoing challenges and prospective advancements aimed at enhancing segmentation efficacy in medical imaging. © 2025 IEEE.

关键词： Convolutional neural networks

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International conference on Computer Graphics, Visualization, Computer Vision and image processing 2021, CGVCVIP 2021, Connected Smart Cities 2021, CSC 2021 and Big Data Analytics, Data Mining and Computational Intelligence 2021, BIGDACI 2021 - Held at the 15th Multi-conference on Computer Science and Information systems, MCCSIS 2021

International Conference on Computer Graphics, Visualization...

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International conference on Computer Graphics, Visualization, Computer Vision and image processing 2021, CGVCVIP 2021, Connected Smart Cities 2021, CSC 2021 and Big Data Analytics, Data Mining and Computational Intelligence 2021, BIGDACI 2021 - Held at the 15th Multi-conference on Computer Science and Information systems, MCCSIS 2021

ISBN: (纸本)9789898704320

The proceedings contain 24 papers. The topics discussed include: using fast multidimensional projections to reveal band and circumplex patterns in reorderable matrices;a 3D spectral-spatial classification of hyperspectral remote sensing imagery using inception based network;3D face reconstruction from hard blended edges;capsule neural networks in classification of skin lesions;a single RGB image based 3D object reconstruction system;face features-based personality assessment;analysis of capsule networks for image classification;analysis and visual exploration of prediction algorithms for public bicycle sharing systems;and hello, my name is smarttram, human factors is on board, enjoy the ride! developing a human factors program for automatic trams.

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