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检索条件"任意字段=Conference on Wavelet Applications in Signal and Image Processing V"

共 4563 条记录，以下是31-40 订阅

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A Convolutional Recurrent Mixer Network For Radar Meteorological image Super-Resolution

A Convolutional Recurrent Mixer Network For Radar Meteorolog...

引用

International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Rafael Gonçalves Pires Daniel F. S Santos Roberto v. Calheiros João Paulo Papa Ik Hyun Lee Sambit Bakshi Khan Muhammad Department of Computing São Paulo State University Bauru Brasil Meteorological Research Institute São Paulo State University Bauru Brasil Dept. of Mechatronics Engineering Tech University of Korea IKLAB Inc. South Korea Dept. of CS&E National Institute of Technology Rourkela India School of Convergence Sungkyunkwan University Seoul South Korea

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

image super-resolution (SR) focuses on reconstructing high-resolution images from their low-resolution counter-parts, often affected by sensor limitations or environmental factors. Convolutional Neural Networks (CNNs) are state-of-the-art for SR tasks but computationally heavy. This paper introduces a novel CRMN (Convolutional Recurrent Mixer Network), a hybrid deep learning-based SR technique designed to address the complexity of CNNs, which is validated in the context of meteorological radar images. Experiments on public benchmark datasets (Berkley432 and T291) and our newly manually collected precipitation dataset from the Meteorological Research Institute (IPMET) show that our CRMN model provides competitive results compared to leading SR methods with significantly fewer parameters, making it a promising and practical solution for SR applications, particularly radar meteorology.

关键词： image quality Meteorological radar Convolution Computational modeling Superresolution Real-time systems Complexity theory Speech processing Mixers signal resolution

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Positive Enhanced Preference Alignment for Text-to-image Models

Positive Enhanced Preference Alignment for Text-to-Image Mod...

引用

International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Haoyuan Sun Bo Xia Yifei Zhao Yongzhe Chang Xueqian Wang Shenzhen International Graduate School Tsinghua University Shenzhen China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Direct Preference Optimization (DPO) has recently expanded its successful application beyond aligning large language models (LLMs), further targeting the alignment of text-to-image models with human preferences. However, traditional DPO approach would inadvertently result in a simultaneous reduction of sampling probabilities for preferred and dispreferred items during the alignment process, thereby potentially diminishing model's generative capacity. In this paper, we firstly undertake a revisit of DPO by grounding our analysis in the framework of contrastive loss. It reveals that DPO only emphasizes the part quantifying dissimilarity between items, while overlooking aspects pertinent to positive items. Hence, we propose the Positive Enhanced Preference Alignment (PEPA). Three enhancement strategies are introduced herein, and after comprehensive empirical evaluation, we recommend implementation of enhancing the log probability of preferred ratio in practice applications, which is distinguished by both stability and effectiveness. Experimental assessments are carried out on the HPS-v2 test set, with results demonstrating that PEPA outperforms or matches current state-of-the-art alignment techniques, thus highlighting PEPA's exceptional practical efficacy.

关键词： Grounding Large language models Text to image signal processing Stability analysis Acoustics Speech processing Thermal stability Optimization Capacity planning

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Cross-Component Residual Prediction for Geometry-Based Point Cloud Compression

Cross-Component Residual Prediction for Geometry-Based Point...

引用

International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Bharath vishwanath Yingzhan Xu Kai Zhang Li Zhang Bytedance Inc. San Diego CA USA

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Point cloud compression is pivotal for the success of immersive multimedia applications. For attribute compression in geometry-based point cloud compression (G-PCC), Region Adaptive Hierarchical Transform (RAHT) is the preferred coding method. Inspired by the significant impact of cross-component prediction in traditional image and video coding, we investigate and present our pioneering work on cross-component residual prediction for RAHT in G-PCC. The method builds on the core observation that cross-component correlations are observed locally in some regions in some sequences. Accordingly, the prediction is employed for last few layers of RAHT which capture local characteristics. We employ a simple linear model, that predicts chroma residues from reconstructed luma residue. The prediction coefficients are learnt on the fly from reconstructed residues of the neighbors. The method gives 1% luma coding gain and around 2-3% chroma coding gain with negligible increase in complexity. The method is adopted to the Geometric Solid Test Model (GeS-TM v7.0), a dedicated codec being developed for solid point clouds.

关键词： Point cloud compression video coding Correlation Transforms Streaming media Solids Encoding Complexity theory Speech processing image reconstruction

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Optimization of Memory Usage in High-Speed Cameras using FPGA

Optimization of Memory Usage in High-Speed Cameras using FPG...

引用

Electronics and Renewable Systems (ICEARS), International conference on

作者： Kavin Kumar K Neelam Sanjeev Kumar Senthilkumar C velmurugan v G Sangar Gokul Chandrasekaran Department of Electronics and Communication Engineering Kongu Engineering College Erode India Department of Computer Science and Engineering (E.Tech.) SRM Institute of Science and Technology Chennai India Department of Electronics and Communication Engineering SIMATS Engineering SIMATS University Chennai Tamil Nadu Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tamilnadu India Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai India Department of Electronics and Communication Engineering Karpagam Institute of Technology Coimbatore India

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509682

High-speed cameras generate large amounts of data, making memory optimization difficult for real-time processing. This project minimizes data size by converting RGBA (Red, Green, Blue, Alpha) images to RGB, eliminating the Alpha channel to reduce memory usage. The captured images are provided as input to verilog code in hexadecimal format, with the conversion done by MATLAB. Bilinear Interpolation is applied to reduce the potential quantization errors during the conversion, using the values of four surrounding pixels to smooth the image and maintain quality. After processing, the image is reconstructed using MATLAB, ensuring the integrity of the output. By utilizing the parallel processing capabilities of FPGAs, this method ensures real-time performance while optimizing memory usage. It is ideal for high-speed imaging applications where both efficiency and image quality are crucial.

关键词： Interpolation Renewable energy sources Quantization (signal) Memory management Parallel processing Cameras Real-time systems MATLAB Field programmable gate arrays Optimization

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High-Resolution Speech Restoration with Latent Diffusion Model

High-Resolution Speech Restoration with Latent Diffusion Mod...

引用

International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Tushar Dhyani Florian Lux Michele Mancusi Giorgio Fabbro Fritz Hohl Ngoc Thang vu Sony Europe B.V. Stuttgart Germany University of Stuttgart Germany

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Traditional speech enhancement methods often oversimplify the task of restoration by focusing on a single type of distortion. Generative models that handle multiple distortions frequently struggle with phone reconstruction and high-frequency harmonics, leading to breathing and gasping artifacts that reduce the intelligibility of reconstructed speech. These models are also computationally demanding, and many solutions are restricted to producing outputs in the wideband frequency range, which limits their suitability for professional applications. To address these challenges, we propose Hi-ResLDM, a novel generative model based on latent diffusion designed to remove multiple distortions and restore speech recordings to studio quality at a full-band sampling rate of 48kHz. Benchmarked against state-of-the-art methods that leverage GAN and Conditional Flow Matching (CFM) components, Hi-ResLDM demonstrates superior performance in regenerating high-frequency-band details. Hi-ResLDM not only excels in non-instrusive metrics but is also consistently preferred in human evaluation and performs competitively on intrusive evaluations, making it ideal for high-resolution speech restoration.

关键词： Measurement Acoustic distortion Computational modeling Speech enhancement Stability analysis image restoration Recording Iterative methods image reconstruction Wideband

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A Comprehensive Review of Hybrid v2X Communication and Edge processing Techniques for Real-Time Emergency vehicle Detection and Prioritization in Urban Traffic Systems

A Comprehensive Review of Hybrid V2X Communication and Edge ...

引用

Device Intelligence, Computing and Communication Technologies, (DICCT), International conference on

作者： Jerim Justin Lokkeshkumar R vijayasri P Department of Electronics and Communication Engineering Chennai Institute of Technology Chennai Tamil Nadu India

ISBN: (数字)9798331543358

ISBN: (纸本)9798331543365

This review paper presents the use of hybrid vehicle-to-Everything (v2X) communication systems to detect and prioritize emergency vehicles in congested urban areas. To reduce response times, researchers are merging edge processing with Dedicated Short-Range Communication (DSRC) and Cellular vehicle-to-Everything (C-v2X). The technology provides extremely fast, low-latency connections, which are essential for real-time applications, by utilizing recent developments in 5G and edge computing. To increase detection accuracy in noisy urban settings, researchers are experimenting with multi-sensor fusion systems that combine GPS, acoustic sensors, and AI-powered vision. Adaptive traffic signal preemption algorithms that dynamically modify traffic flows to grant priority access to emergency vehicles are also being investigated in some research. Despite its promise, there are still obstacles to be addressed, such as interoperability problems and network congestion. However, the benefits might be enormous: quicker emergency reactions, more seamless traffic patterns, and generally more effective urban transportation systems. In the upcoming years, we should witness some fascinating breakthroughs as researchers continue to hone these technologies.

关键词： Accuracy Reviews 5G mobile communication image edge detection Urban areas vehicular ad hoc networks Real-time systems Dedicated short range communication vehicle-to-everything Edge computing

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Speech recognition by neural networks and pre-processing wavelet

Speech recognition by neural networks and pre-processing wav...

引用

conference on wavelet applications in signal and image processing v

作者： Cister, AM Galante, GMF Federal Univ. of Rio de Janeiro (Brazil)

ISBN: (纸本)0819425915

Our goal in this article is to present a quantitative study about speech recognition and the inherent problems of its applications and the computer processing. Our approach is characterized by independent speaker and we made use of pre-processing the concept as wavelets Transform and as pattern recognition an Artificial Neural Network (ANN - Multilayer Perceptron -Backpropagation Algorithm).

关键词： speech recognition wavelet transform artificial neural network filters bank

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Matched wavelet analysis of single differential EMG signals

Matched wavelet analysis of single differential EMG signals

引用

conference on wavelet applications in signal and image processing v

作者： Olmo, G Laterza, F Politecnico di Torino (Italy)

ISBN: (纸本)0819425915

EMG signals can be considered as the sum of scaled and delayed versions of a single prototype. We have applied the wavelet Transform choosing the mother wavelet so as to match the known shape of the basic component, and have compared the results obtained with different wavelets. The results in terms of MUAP detection and resolution are very encouraging even in the presence of asymmetric shape and high levels of additive noise.

关键词： EMG signal biomedical applications matched wavelet transform denoising

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On consistent signal reconstruction from wavelet extrema representation

On consistent signal reconstruction from wavelet extrema rep...

引用

conference on wavelet applications in signal and image processing v

作者： Lu, J Apple Computer Compression and Signal Processing Dept. MS 302-3MT Cupertino CA 95014 2 Infinite Loop United States

ISBN: (纸本)0819425915

This paper studies the algorithms that reconstruct a signal from its wavelet extrema representation. We show that the existing reconstruction algorithms are inadequate in assuring a consistent reconstruction. We further propose a method that can be used with a number of existing algorithms to guarantee a consistent reconstruction. The new method provides a rigorous way to prevent artifacts resulting from the spurious wavelet extrema in the reconstructed signal.

关键词： signal reconstruction multiscale edges wavelet extrema wavelets

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Satellite image compression by directional decorrelation of wavelet coefficients

Satellite image compression by directional decorrelation of ...

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33rd IEEE International conference on Acoustics, Speech and signal processing

作者： Delaunay, X. Chabert, M. Charvillat, v. Morin, G. Ruiloba, R. NOVELTIS CNES TeSA Toulouse France ENSEEIHT IRIT Toulouse France NOVELTIS Romainville France

ISBN: (纸本)9781424414833

This paper presents a satellite image compression scheme based on a post-processing of the wavelet transform of images. The bandelet transform is a directional post-processing of wavelet coefficients. Thanks to a low computational complexity, this transform is a good candidate for future on-board satellite image compression systems. First, we analyze the ability of the bandelets to exploit directional correlations between wavelet coefficients. This study leads to an improved post-processing with a better decorrelation of adjacent wavelet coefficients in the vertical or in the horizontal direction taking into account the wavelet subband orientations. To perform even better decorrelation, bases are also build by Principal Component Analysis (PCA). This results in an improved compression performance without increasing the computational complexity.

关键词： image coding wavelet transforms decorrelation discrete transforms satellite applications

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