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检索条件"任意字段=Conference on Applications of Digital Image Processing XLII"

共 10205 条记录，以下是41-50 订阅

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Automatic Filtreing of Quasy-Periodic Noise

Automatic Filtreing of Quasy-Periodic Noise

引用

digital Signal processing and its applications (DSPA), International conference on

作者： Anatoly Novikov Vladimir Ovchinnikov Ryazan State Radio Engineering University named after V.F. Utkin Ryazan Russia

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

The problem of filtering periodic noise in digital images in an automatic mode has been addressed by scientists in many countries. Several alternative methods have been proposed. Currently, approaches to solving the problem of quasi-periodic noise filtering in automatic mode are actively being investigated. This type of noise is more common in real images. This paper briefly discusses the methods that best meet the criteria for quasi-periodic noise filtering quality and computational complexity requirements. Additionally, a formalized description of the iterative method proposed by the authors is provided, along with the results of experimental studies comparing the proposed method with other approaches.

关键词： Fourier transforms Filtering digital images Noise Noise reduction Signal processing algorithms digital signal processing Iterative algorithms image restoration Computational complexity

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Wavelet-based Filtering of Noisy images by Amplification of Low-Frequency Components in High-Frequency Subbands

Wavelet-based Filtering of Noisy Images by Amplification of ...

引用

digital Signal processing and its applications (DSPA), International conference on

作者： Y. S. Bekhtin V. T. Trinh Department of Automatics and Information Technologies in Control Ryazan State Radio Engineering University named after V.F. Utkin Ryazan Russian Federation

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

The paper describes a new method of noisy image restoration based on amplification of low-frequency components in high-frequency subbands, or details of fast wavelet transform (FWT). It makes a difference with respect to well-known wavelet filtering methods which are typically based on soft thresholding of wavelet coefficients belonging to high-frequency subbands of a noisy image. At the same time, the low-frequency component, or approximation can be used to extract the low-frequency components corresponding the details. It allows modifying the details of the FWT by adding the extracted low-frequency components that leads to increasing the signal-to-noise ratios in subbands. The paper contains the experimental results of modeling proving the effectiveness of the suggested method comparing to some widely used filtering methods, too. The results of modeling have shown that the proposed method allows improving quality of restored image by increasing both the signal-to-noise ratio and significantly reducing the number of ringing artifacts.

关键词： Wiener filters Filtering image edge detection digital signal processing image restoration Noise measurement Signal to noise ratio Wavelet coefficients

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Detection of Offline Handwritten Signature Forgery Using InceptionV4 with Sobel Edge Detection

Detection of Offline Handwritten Signature Forgery Using Inc...

引用

digital Signal processing and its applications (DSPA), International conference on

作者： Ericka F. Rudico John Mar Y. Armocilla Meo Vincent C. Caya School of Electrical Electronics and Computer Engineering Mapúa University Manila Philippines

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

Handwritten signature forgery detection is essential for authenticating signatures to address the risks of document falsification, identity theft, and financial fraud from signature forgeries. This study presents a reliable approach to accurately classify genuine and forged signatures using deep learning and image pre-processing techniques. Specifically, the proposed method utilizes InceptionV4 with Sobel edge detection. InceptionV4, a deep convolutional neural network, is used to extract features from signature images, while Sobel edge detection enhances these features. By applying Sobel edge detection during the image pre-processing stage, we emphasize the edges of the signatures, which aids in the classification process. Furthermore, we implemented data augmentation techniques to effectively generate additional datasets, overcoming the significant limitations of the lack of custom signature datasets. By integrating Inception V4’s capabilities and Sobel edge detection, the model achieved a high accuracy of 96.19% and an F1-score of 96.18%. These results demonstrate the potential and effectiveness of the proposed approach in detecting signature forgeries.

关键词： Deep learning image edge detection Identity theft Finance digital signal processing Feature extraction Data augmentation Forgery Reliability Convolutional neural networks

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Design and Analysis of Compressor Using Approximate Full Adders for Future Low power Electronics

Design and Analysis of Compressor Using Approximate Full Add...

引用

International conference on Wireless Communications, Signal processing and Networking (WiSPNET)

作者： MD Badhesha Arun Sekar Rajasekaran Yenimireddy Sandhya Aluvoju Vivek Dept. of ECE SR University Warangal Telangana India

ISBN: (数字)9798331524227

ISBN: (纸本)9798331524234

In the digital world, approximate computation approaches are being investigated to minimize complexity and power consumption by permitting minor errors in applications like digital signal processing. The proposed approximate full-adder compressor offers significant improvements compared to the exact full-adder-based compressor. Specifically, the area is reduced by 53.85%. Furthermore, the delay in the proposed AFA compressor is reduced by 58% compared to the traditional full-adder compressor. Regarding power consumption, the proposed AFA is highly efficient and consumes 66% less power than the exact compressor. Furthermore, the proposed AFA reduces PDP by 86.72%. A Python script on the Google Collab platform calculates performance measures for image processing applications, including the Peak Signal-To-Noise Ratio, Mean Squared Error, Mean Absolute Error, and Structural Similarity Index Measure. A 45nm technology file is used to assess computational findings using the Cadence tool.

关键词： Wireless communication Performance evaluation image coding Power demand PSNR Measurement uncertainty Personal digital devices Low power electronics Delays Adders

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Compact and Efficient Neural Networks for image Recognition Based on Learned 2D Separable Transform

Compact and Efficient Neural Networks for Image Recognition ...

引用

digital Signal processing and its applications (DSPA), International conference on

作者： Maxim Vashkevich Egor Krivalcevich Department of Computer Engineering Belarusian State University of Informatics and Radioelectronics Minsk Belarus

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

The paper presents a learned two-dimensional separable transform (LST) that can be considered as a new type of computational layer for constructing neural network (NN) architecture for image recognition tasks. The LST based on the idea of sharing the weights of one fullyconnected (FC) layer to process all rows of an image. After that, a second shared FC layer is used to process all columns of image representation obtained from the first layer. The use of LST layers in a NN architecture significantly reduces the number of model parameters compared to models that use stacked FC layers. We show that a NN-classifier based on a single LST layer followed by an FC layer achieves 98.02% accuracy on the MNIST dataset, while having only 9.5k parameters. We also implemented a LST-based classifier for handwritten digit recognition on the FPGA platform to demonstrate the efficiency of the suggested approach for designing a compact and high-performance implementation of NN models.

关键词： Accuracy image recognition Quantization (signal) Two-dimensional displays Transforms Artificial neural networks Computer architecture image representation Field programmable gate arrays image classification

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Wavelet Analysis of Cardiograms in EDF Format

Wavelet Analysis of Cardiograms in EDF Format

引用

digital Signal processing and its applications (DSPA), International conference on

作者： Sinan V. Kurbanov Denis A. Andrikov Department of Mechanics and Control Processes Peoples' Friendship University of Russia (PFUR) Moscow Russian Federation

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

The correlation of the wavelet shape and the characteristic ECG section has been confirmed, and wavelets for the identification of P-, R-, and T waves have been experimentally established. An algorithm for identifying R waves in an ECG has been developed and its operability has been verified. Using the algorithm developed, a graph of the dynamics of the heartbeat period is plotted as a function of time (period number). To identify the P and T waves, the wavelet image of the real ECG is constructed, and the presence of distortion of the shape of this image due to the influence of QRS complex and neighboring waves is established. Computer removal (filtering) of QRS complexes from the ECG is carried out, wavelet image of the remaining part is calculated. The possibility of determining the positions of the maximum P- and T-waves has been established from the wavelet image of the filtered ECG. The theoretical and practical value of this study consists in a new direction of wavelet analysis of cardiac signals, by successively applying several wavelets of a special form, to identify characteristic sections of the ECG in order to improve diagnostics. The proposed method also assumes intermediate filtering of the identified sections when moving from wavelet to wavelet. The development was carried out within the framework of computer generation of arrays of digital functions of the state of the heart, suitable for training artificial intelligence systems, and diagnostics using such systems. The practical results obtained can be applied in the development of a digital expert diagnostic system or a specific technical device.

关键词： Training Correlation Shape Heart beat Filtering Heuristic algorithms Signal processing algorithms Electrocardiography Wavelet analysis Distortion

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A Machine Learning Framework for Skin Cancer Detection using Transfer Learning

A Machine Learning Framework for Skin Cancer Detection using...

引用

International image processing, applications and Systems conference (IPAS)

作者： Mary Linda Panakal Augustine Sotirios Spanogianopoulos Mhd Saeed Sharif Department of Computer Science and Digital Technologies School of Architecture Computing and Engineering University of East London London UK School of Electrical and Mechanical Engineering University of Portsmouth Portsmouth UK

ISBN: (数字)9798331506520

ISBN: (纸本)9798331506537

This paper uses deep learning algorithms including InceptionV2, InceptionV3, DenseNet, MobileNet, and VGG19 to improve skin cancer detection. This research aims to improve skin cancer diagnosis. This work aims to determine the most effective evolutionary metrics-based technique to recognizing skin cancer, which is comparable to other diseases. Ultimately, our paper aims to create a realistic skin cancer detection system that uses the best deep learning algorithm. This discovery might improve medical diagnostics, leading to earlier diagnosis and improved healthcare outcomes.

关键词： Deep learning Machine learning algorithms image processing Transfer learning Medical diagnosis Reliability Skin cancer image classification

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Deep Learning Technique for Computer Vision-Based Pose Estimation for Augmented Reality 3rd

Deep Learning Technique for Computer Vision-Based Pose Estim...

引用

3rd International conference on Intelligent Computing Techniques for Smart Energy Systems, ICTSES 2023

作者： Palanimeera, J. Ponmozhi, K. Jyothi, Kanagaraj Dargar, Shashi Kant Birla, Shilpi Department of Computer Applications Sathyabama Institute of Science and Technology Chennai India Department of Computer Applications Kalasalingam Academy of Research and Education Krishnan Kovil Tamil Nadu Virudhunagar India Department of Biotechnology Kalasalingam Academy of Research and Education Krishnan Kovil Tamil Nadu Virudhunagar India Department of Electronics and Communication Engineering Kalasalingam Academy of Research and Education Krishnan Kovil Tamil Nadu Virudhunagar India Department of Electronics and Communication Engineering Manipal University Jaipur Rajasthan Jaipur India

ISBN: (纸本)9789819784288

Pose estimation approaches of open pose were suggested. Pose estimation in real-time is a difficult research subject with many computer vision applications. Pose estimation applications are Human Activity Estimation, Motion Transfer and Augmented Reality, Training Robots, Motion Tracking for Consoles, and Human Fall Detection. This paper describes the Augmented Reality (AR) of pose estimation. AR is an enhanced version of the real physical world that is achieved through the use of digital visual elements, sound, or other sensory stimuli delivered via technology. One interesting use for obtaining the Open-Pose discovered important locations in each pose is in the field of augmented reality. A technique for 3D model overlays on an image using pose key point information that is presented in this study. To extract crucial information from the data, the fully convolutional networks deep learning technique is used. The technique used in this work comprises the real-time intersection of the picture plane with the intended 3D model and accurate model orientation based on the key point data. The performance will greatly depend on the Graphics processing Unit specifications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep learning

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Comparative Study of Autoencoders Used for Noisy images Restoration

Comparative Study of Autoencoders Used for Noisy Images Rest...

引用

digital Signal processing and its applications (DSPA), International conference on

作者： Y.S. Bekhtin P.E. Zhgutov Department of automatics and information technologies in control Ryazan State Radio Engineering University named after V.F. Utkin Ryazan Russia

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

The paper is devoted to solving the problem of restoring noised images by convolutional autoencoders. It is provided a comparative research of three types of convolutional autoencoder architectures: the standard architecture based on convolution and deconvolution operations; the architecture based on Residual-blocks; the architecture based on Residual-blocks using a discriminator network. The effectiveness of the autoencoder architectures have been evaluated on synthetically noisy color images. Subjective and objective metrics as MSE, RMSE, PSNR, SSIM were used to evaluate the quality of the restored images. In the course of a comparative study, some recommendations were drawn on which of the explored autoencoders to choose providing the best effectiveness restoring the quality of distorted images.

关键词： Deconvolution Convolution Autoencoders Computer architecture digital signal processing image restoration Computational efficiency Noise measurement Convolutional neural networks Standards

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Application of UAV, GNSS and InSAR Techniques in the Raw Material Supply Chain 11

Application of UAV, GNSS and InSAR Techniques in the Raw Mat...

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11th International conference on Geographical Information Systems Theory, applications and Management, GISTAM 2025

作者： Grabrijan, Tanja Oštir, Krištof Trajkovski, Klemen Kozmus Grigillo, Dejan Horvat, Veronika Grabrovec Prešeren, Polona Pavlovčič Hamza, Veton Pepe, Antonio Calò, Fabiana Falabella, Francesco Sanz-Ablanedo, Enoc Gheorghe, Mihaela Selea, Teodora Teodoro, Ana Cláudia University of Ljubljana Faculty of Civil and Geodetic Engineering Jamova cesta 2 Ljubljana Slovenia Diocleziano Napoli328 Italy Universidad de León León Spain GMV Innovating Solutions SRL Bucharest Romania Rua do Campo Alegre 687 Porto Portugal

ISBN: (纸本)9789897587412

The marble quarry, located in southern Austria produces high-quality marble, both in open-pit and underground extraction sites. Extraction, transportation and accumulation of material require close monitoring to maintain the stability of the whole area and to observe changes in waste dumps. In this study, we have shown how different methodologies can be used to support the monitoring of the entire raw material supply chain. Several unmanned aerial vehicle (UAV) surveys were performed to compute high-resolution digital elevation models (DEM) to serve as a reference for comparing stereo and tri-stereo DEMs calculated from satellite imagery. A low-cost global navigation satellite system (GNSS)-based monitoring system was set up to estimate horizontal and vertical displacements. In addition, the state-of-the-art technique of Interferometric synthetic aperture radar (InSAR) provided displacement time series for a broader area. © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Stereo image processing

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