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

共 13664 条记录，以下是1051-1060 订阅

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Laplacian of Gaussian Based on Color Constancy Algorithm for Surrounding image Stitching Application

Laplacian of Gaussian Based on Color Constancy Algorithm for...

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IEEE International conference on Consumer Electronics - Taiwan (ICCE-TW)

作者： Lee, Tsung-Han Chou, He-Sheng Chen, Tsung-Yi Lo, Wen-Shen Zhang, Jun-Ting Chen, Chiung-An Lin, Ting-Lan Chen, Shih-Lun Chung Yuan Christian Univ Dept Elect Engn Taoyuan Taiwan Ming Chi Univ Technol Dept Elect Engn New Taipei Taiwan Natl Taipei Univ Technol Dept Elect Engn Taipei Taiwan

ISBN: (数字)9781665470506

ISBN: (纸本)9781665470506

This paper presents a new algorithm for Laplacian of Gaussian (LoG) image processing systems. In order to improve nowadays digital capture system and digital display calibration. Color constancy is added to improve the measurement of object color based on independent light sources. To satisfy the human eye's recognition of colors, the angular error must be corrected to make the light source reflect naturally in the image. In addition, the hardware design of classic white balance algorithms such as Gray-World, Max-RGB, and Gray-Edge with the Minkowski norms is implemented in this study. The proposed algorithm is simulating with a Gaussian filter and an additional Laplacian of Gaussian (LoG) to generate real-time masks that automatically brighten images. Compared with several previous studies, the proposed algorithm shows lower angular errors while maintaining the quality of the graphics. The motivation is to make better quality watches on display facilities and better capture systems.

关键词： White Balance Color Constancy Gaussian filter Laplacian of Gaussian(LoG) Gray-World Max-RGB Gray-Edge Minkowski norm Angular error

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Robust Calibration for Enhanced Imaging in Near-Field D-Band MIMO Radar systems

Robust Calibration for Enhanced Imaging in Near-Field D-Band...

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European conference on Antennas and Propagation, EuCAP

作者： Lorena Perez-Eijo Marcos Arias Borja Gonzalez-Valdes José Vázquez-Cabo Ignacio Sardinero–Meirás Jesus Grajal AtlanTTic Research Center Universidade de Vigo Vigo Spain Information Processing and Telecommunications Center Universidad Politécnica de Madrid Madrid Spain

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

This work introduces a calibration algorithm designed to improve high-precision imaging in real-time MIMO radar systems. The algorithm applies the Inverse Fourier Transform (IFFT) and advanced signal processing techniques to efficiently extract and process key data from raw measurements, focusing on critical Regions Of Interest (ROI) while filtering out unnecessary information. A robust phase correction mechanism ensures precise calibration and alignment, preventing phase errors that could otherwise lower image quality. The algorithm provides an effective balance between computational efficiency and the high accuracy required by modern MIMO radars, paving the way for further improvements in real-time imaging.

关键词： MIMO radar Signal processing algorithms Coherence Radar imaging Signal processing Real-time systems Hardware Calibration Spatial resolution image reconstruction

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Research on Efficient image Feature Extraction based on Low-Rank Representation for Intelligent Reading systems

Research on Efficient Image Feature Extraction based on Low-...

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image processing, Electronics and Computers (IPEC), Asia-Pacific conference on

作者： Yulan Tan Heilongjiang University of Technology Jixi China

ISBN: (数字)9798350374407

ISBN: (纸本)9798350374414

Efficient and accurate extraction of image features is essential for ensuring high-performance information transmission in intelligent reading systems. This paper introduces a computer-assisted method for intelligent image feature extraction, specifically focusing on the Low-Rank Representation (LRR) approach. The study addresses challenges presented by noisy and diverse character or image data encountered in real-world scenarios. By employing LRR, the accuracy of image extraction, which includes object recognition and scene understanding, is significantly enhanced. Subsequently, the proposed techniques for intelligent image feature extraction undergo comprehensive evaluation, assessing both effectiveness and versatility through extensive experiment verifications. The experimental results validate the efficacy of the proposed method and demonstrate its superior image content extraction accuracy compared to existing methods. This proposed method provides crucial assistance to high-performance intelligent reading systems, thereby enhancing its applicability for potential consumers.

关键词： YOLO Visualization Accuracy Process control Feature extraction Rendering (computer graphics) Classification algorithms Data mining Proposals Principal component analysis

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image Quality Assessment for Computer Vision Based Perception algorithms Using Edge and Structural Features 38

Image Quality Assessment for Computer Vision Based Perceptio...

引用

38th IEEE Region 10 conference, TENCON 2023

作者： Akshaya, V.G. Rithika, S. Lanciya Angel, A. Amirtha Pravin, K.S.M. Balasubramanian, Karthi Srinivasan, Suganthi Rajegowda, Rakesh Bhattacherjee, Payal Amrita School of Engineering Amrita Vishwa Vidyapeetham Department of Electronics and Communication Engineering Coimbatore India R & D-Computer Vision Systems Valeo India Pvt.ltd Comfort Driving Assistance Group Chennai India

ISBN: (纸本)9798350302196

image Quality Assessment (IQA) is a critical task in image processing, computer vision, and other related fields, as it helps in evaluating the effects of various impairments on the Quality of Experience (QoE) of consumers. However, current IQA metrics may have limitations in evaluating image quality accurately for different types of images or under different conditions. To address this, a proposed approach involves calculating an overall image quality score based on linear combination of individual image quality metrics. This method considers multiple image features such as sharpness, contrast, color, and noise, and assigns weights to each feature based on its relative importance in determining overall image quality. By combining and weighting multiple image features, the proposed approach aims to provide a more comprehensive and accurate evaluation of image quality compared to using individual metrics alone. In this study, we focus on the importance of edge features and structure-based metrics in object detection and analyze existing No-Reference (NR) IQA metrics, including Just Noticeable Blur (JNB), Cumulative Probability Blur Detection (CPBD), Visual Quality Assessment (VQA), Blind/Referenceless image Spatial Quality Evaluator (BRISQUE) and No-Reference Low- Light image Enhancement Evaluation (NLIEE), and propose a linear combination formula that combines these metrics to evaluate image. We evaluate the performance of the proposed metric on several datasets by calculating the linear combination of two, three, and all the five metrics. The weights assigned to each metric in the linear combination formula are determined through experimental analysis. The combined metric scores and MOS scores are then used to compute the Spearman's rank order correlation coefficient, which measures the monotonic relationship between two variables. A higher SROCC value indicates a stronger correlation between the combined metric and MOS scores and is used to evaluate the performanc

关键词： image quality

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Enhanced K-means Color Clustering Based on SLIC Superpixels Merging incorporated within the Entomology Software: AInsectID

Enhanced K-means Color Clustering Based on SLIC Superpixels ...

引用

IEEE Workshop on Evolving and Adaptive Intelligent systems (EAIS)

作者： Haleema Sadia Parvez Alam School of Engineering The University of Edinburgh Edinburgh Scotland UK

ISBN: (数字)9798350366235

ISBN: (纸本)9798350366242

Superpixel-based segmentation is an important pre-processing step for the simplification of image processing. The subjective nature behind the determination of optimal cluster numbers in segmentation algorithms can result in either underor over-segmentation burdens, depending on the image type. Insect wings, with their intricate color patterns, pose significant challenges for the accurate capture of color diversity in clustering algorithms, assuming a spherical and isotropic cluster distribution is used. This paper introduces a hybrid approach for color clustering in insect wings, integrating the Simple Linear Iterative Clustering (SLIC) method to generate the initial superpixels, and a DeltaE 2000 function the precisely discriminated merging of superpixels. Color differences between superpixels serve to measure homogeneity during the merging process. The proposed new algorithm demonstrates enhanced segmentation as it overcomes the issue of over-segmentation and under-segmentation, as evidenced by the results derived from the Boundary Recall, Rand index, Under-segmentation Error, and Bhattacharyya distance using ground truth data. The Silhouette score and Dunn Index are also used to quantitatively evaluate the efficacy of our new proposed clustering technique.

关键词： image segmentation image color analysis Insects Merging Clustering algorithms Software Hybrid power systems

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Case-Study for Integration of COTS SoC Devices in Reliable Space systems for On-Board processing

Case-Study for Integration of COTS SoC Devices in Reliable S...

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2023 European Data Handling and Data processing conference for Space, EDHPC 2023

作者： Rodriguez-Ferrandez, ivan Steenari, David Tali, Maris Kosmidis, Leonidas Tonicello, Ferdinando Barcelona Spain Barcelona Spain Noordwijk Netherlands

ISBN: (纸本)9789090379241

Recent trends in Data Handling systems (DHS) include increased data-rates, in-orbit reconfiguration and the introduction of advanced On-Board processing (OBP) methods to extract actionable information on-board, with low latency. At the same time, NewSpace industry has successfully deployed COTS-based DHS and processing equipment in space. In particular for OBP, COTS-based processors and FPGAs can offer higher computational performances than space qualified equivalents-which in turn can enable new applications through more advanced OBP algorithms. The individual component cost is also lower for COTS than space qualified components, which can allow overall cost-optimisations on mission *** internal working group at ESA has studied the concept of using "safety barriers"to ensure no propagation of failure from functions implemented with COTS to other on-board units. Thanks to ESA studies there is a path to use Class iv equipment on missions with higher class (Class I-III), through the use of hardware "safety barriers"to limit failure propagation from Commercial Off-The-Shelf (COTS) *** our work, we take the above mentioned concepts and apply them to reference implementations, targeting payload processing modules based on standard form factors (ADHA) and automotive-grade GPU systems-on-Chip (SoCs). In addition, we make use of previous work on improving in-flight availability of complex COTS SoC processors, through system and software Fault Detection, Isolation and Recovery (FDIR) techniques. © 2023 ESA.

关键词： System-on-chip

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International conference on Advances in Data Science and Computing Technologies, ASDC 2022

International Conference on Advances in Data Science and Com...

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International conference on Advances in Data Science and Computing Technologies, ASDC 2022

ISBN: (纸本)9789819936557

The proceedings contain 77 papers. The special focus in this conference is on International conference on Advances in Data Science and Computing Technologies. The topics include: Effect of Dropout on Convolutional Neural Network for Hyperspectral image Classification;state Derivative Optimal Control Law for Submersible Autonomous Robotic Vehicle in Steering Plane;ASR for Indian Regional Languages Using Fine-Tuned Wav2Vec2 Model;Intelligent Online Voting System for Twenty-First Century and Smart Cities 5.0: An Empirical Approach through Blockchain with ML Techniques;an Empirical Study on Credit Risk Assessment Using Ensemble Classifiers;audio Based Text Summarization Using Natural Language processing;blockchain-Enabled Security in Vehicular Ad Hoc Network;stock Selection Using Ontological Financial Analysis;Prediction of Future Career Course of Students Through RF Algorithm;components of Information Diffusion and Its Models in Online Social Networks;a Comparative Study;development of a Residual Neural Network Architecture for the Detection of Diabetic Retinopathy in Retinal Fundus images;prediction Markets Using Machine Learning;evaluation of Optimum Batting Order Based on Partnership Analysis Using Ant Colony Optimization Technique;identification of Rock images in Mining Industry: An Application of Deep Learning Technique;evaluation of Teachers’ Performance Using Fuzzy Inferences System;a Detailed Analysis on Intrusion Detection systems, Datasets, and Challenges;object Detection Under Low-Lighting Conditions Using Deep Learning Architectures: A Comparative Study;terahertz image processing: A Boon to the Imaging Technology;developing a Talent Identification Model for Predicting Player Position in Football Using Machine Learning algorithms;Survey of Various Machine Learning Techniques for Analyzing IoMT-Based Remote Patient Monitoring System;PSO-Based Traffic Signals in a Real-World City.

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Transform-domain image Enhancement for Underwater Visual SLAM based on Homomorphic Filter

Transform-domain Image Enhancement for Underwater Visual SLA...

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image processing, Computer Vision and Machine Learning (ICICML), International conference on

作者： Shuo Zhang Chaoyu Zhang Wei Wang Xinrui Zeng Bin Luo State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan China China Nuclear Power Operation Technology Corporation LTD Wuhan China CNNC Engineering Research Center of Nuclear Industry Special Robot Wuhan China

ISBN: (数字)9798350355413

ISBN: (纸本)9798350355420

Underwater visual SLAM algorithms play a vital role in autonomously localizing Autonomous Underwater Vehicles (AUV) in challenging underwater environments. The low-light conditions underwater necessitate the use of artificial lighting sources. However, this can lead to issues such as overexposed or underexposed images, resulting in reduced image contrast and information content. This study introduces a transform-domain image enhancement technique aimed at bolstering the resilience of underwater visual simultaneous localization and mapping (SLAM) systems. Specifically, a homomorphic filtering method is implemented to alleviate the impact of low-frequency lighting variations on images, thereby enhancing overall image clarity and bolstering the performance of visual SLAM systems. The efficacy of this filtering approach is validated through experiments conducted on the AQUALOC dataset. Our findings demonstrate that this method enhances the success rate of visual SLAM tracking, thereby enhancing its utility in AUV localization tasks.

关键词： Location awareness image quality Visualization Autonomous underwater vehicles Simultaneous localization and mapping Filtering Filtering algorithms Feature extraction Artificial light image enhancement

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Research on Graph Neural Network Algorithm and image Recognition Application 20

Research on Graph Neural Network Algorithm and Image Recogni...

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20th International Computer conference on Wavelet Active Media Technology and Information processing, ICCWAMTIP 2023

作者： Xu, Jia-Hao Li, Jian-Ping School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu610054 China

ISBN: (纸本)9798350318982

The emergence of graph neural networks makes up for the limitations of traditional neural networks in dealing with complex graph data, and they are widely used in the fields of social networks and recommender systems, but at the same time, there are some defects in themselves. This paper introduces the basics of graph neural networks, and also summarizes the advantages and disadvantages of GSN, GraphSAGE, DeepWalk and Node2Vec algorithms. Finally, it also discusses the application of graph neural networks in the field of image recognition, summarizes its deficiencies in practical applications, and puts forward the prospect of the future development of graph neural networks. © 2023 IEEE.

关键词： image recognition

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FPGA Interfaced ECG Signal processing Based on Machine Learning Classifier

FPGA Interfaced ECG Signal Processing Based on Machine Learn...

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2023 International conference on Energy, Materials and Communication Engineering, ICEMCE 2023

作者： Jeya Malar, R. Mary Mettilda, J. Mageshbabu, M. Siva Nagini, R. Grace, Lily Saron Gireesha, B. Kings Engineering College Department of Information Technology Chennai India Ppg Institute of Technology Department of Electronics and Communication Engineering Coimbatore India SIMATS Saveetha School of Engineering Department of Electronics and Communication Engineering Thandalam Chennai India Universal College of Engineering and Technology Department of Electrical and Electronics Engineering Tamilnadu Vallioor India Kings Engineering College Department of Electronics and Communication Engineering Chennai India University College of Science Tumkur University Department of Electronics Karnataka572103 India

ISBN: (纸本)9798350393378

This study aims to propose an FPGA-oriented ECG signal processing system architecture. The method identifies FPGA complexes and classifies beats as either preterm or typical contractions of the ventricular wall. For pulse classification, an element of the Open Source ECG Analysis Software is used, and for FPGA complexity verification, a method based on a phase-space image of an ECG signal is used. Artificial intelligence (AI) is increasingly serving as the basis for autonomous and independent systems. One of the most popular machine learning techniques among many categorization strategies is the Support Vector Machine (SVM) classification. We may further improve the SVM classifier's accuracy and classification process by using convex optimization techniques to identify the best solution. Numerous machine learning techniques, such as SVM classification, need a lot of processing power since they are compute-and data-intensive. Additionally, a number of machine learning algorithms have made it into incorporated and handheld gadgets, which have very particular demands. © 2023 IEEE.

关键词： Electrocardiograms

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