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共 4116 条记录，以下是21-30 订阅

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Performance Optimization of FIR Filters Using Approximate Multipliers

Performance Optimization of FIR Filters Using Approximate Mu...

引用

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

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

ISBN: (数字)9798331524227

ISBN: (纸本)9798331524234

Area, Power, and Delay is the fundamental triangular loop on which complete Very Large Scale Integration(VLSI) depends. Achieving a trade-off among these three parameters is a bit challenging. However, approximate computing makes this possible by compromising accuracy at the output, which is acceptable in multimedia applications. Inspired by this, the approximate design of Full Adder, Compressor, and 4x4, 8x8 Vedic Multipliers used in building an FIR low pass filter is proposed to optimize its performance. Those circuit designs are comparatively evaluated with parameters such as area, power, delay, and Power Delay Product in Digital Cadence. Not only the parametric evaluation but also evaluation is done with image addition as an image processing application. Further, the processed image is evaluated with Structural Similarity Index Measure, Peak signal-To-Noise Ratio, Mean Squared Error, and Mean Absolute Error to validate the proposed method. This metrics evaluation is done using Python code.

关键词： Wireless communication image coding Accuracy PSNR Finite impulse response filters Low-pass filters signal processing Delays Convolutional neural networks Adders

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Redefining Well Exposedness for Locally Adaptive Multi-Exposure Fusion

Redefining Well Exposedness for Locally Adaptive Multi-Expos...

引用

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

作者： Prince Arya Saurabh Kumar Ashish Agarwal Nutan Yenneti Narasimha Pai AI Computational Imaging Samsung Research India Bangalore

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Multi-exposure fusion combines bracketed exposure captures into a single image with enhanced details from a large dynamic range. It is an effective and resource-efficient way to obtain a high dynamic range image, which has broad applications. Despite significant advancements in the field, existing methods often struggle with artifacts and fall short of preserving the local details while being compute-intensive. Previous similar training-free approaches compute weight maps for fusing the exposure stack, which requires finding how well-exposed each image is. In this paper, we work on the fundamentals to define a novel, well-exposedness function along with a tile-based processing approach. Our approach provides improved image quality with better detail recovery. It outperforms the current state-of-the-art training-free methods both qualitatively and quantitatively while being better suited for onboard processing.

关键词： image quality Photography signal processing Acoustics High dynamic range Speech processing Smart phones

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Dual-Path Consistency Unsupervised Domain Adaptation for Nighttime Semantic Segmentation

Dual-Path Consistency Unsupervised Domain Adaptation for Nig...

引用

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

作者： Yuwu Lu Jicong Lang Meirong Ding School of Artificial Intelligence South China Normal University Foshan China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Nighttime semantic segmentation is an indispensable component in practical applications, such as automated vehicles. However, it is often hindered by the lack of annotations due to interference caused by inadequate lighting or exposure. To overcome these difficulties, we propose a Dual-Path Consistency (DPC) unsupervised domain adaptation (UDA) approach. One path is image Darkening Path (IDP), in which feature representations of original images and darkened images extracted from the feature encoder are leveraged to maintain cross-domain style consistency. Another path is image Masking Path (IMP), in which the masked images are reconstructed under the guidance of pseudo-labels, aiming to maintain content consistency in an entirely identical scenario. Extensive experiments on four bench-marks demonstrate the superior performance of the proposed DPC for nighttime semantic segmentation.

关键词： Semantic segmentation Semantics Lighting Interference signal processing Benchmark testing Feature extraction image restoration Speech processing image reconstruction

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Underwater image Enhancement Using Gaussian Smoothing and Edge Detection

Underwater Image Enhancement Using Gaussian Smoothing and Ed...

引用

International conference on Inventive Computation Technologies (ICICT)

作者： V. Lambodara Aravind C. Bagyalakshmi Department of Computer Applications Hindustan Institute of Technology and Science

ISBN: (数字)9798331512248

ISBN: (纸本)9798331512255

Underwater acoustic communication is used for oceanographic data collection, environmental monitoring, disaster alarm systems, and navy applications. Underwater has its peculiarities such strong signal attenuation and limited bandwidths, multipath nature of signals, and ambient noises. All these characteristics bring a great deal of interference probably in transmission with certainty and effectiveness. This work propounded an optimized hybrid model that works concurrently with advanced signal processing and noise-reducing techniques for communication enhancement. The purpose of the proposed model is to develop high signal-to-noise ratio (SNR) received signals with lesser transmission error using time-frequency domain analysis and filtering techniques, which are specifically designed for underwater applications. Thus, the main aim of this work, in fact, is towards the development of a robust underwater communication platform, which ensures a very reliable transfer of data under conditions of excessive noise even in the rapidly changing aquatic environments. Comparison of the proposed model with traditional techniques shows that this model stands much higher than the earlier techniques regarding transmission accuracy, noise resilience, and overall efficiency, thus extending the development of more reliable underwater communication systems toward future marine and defense applications.

关键词： Adaptation models Underwater communication Smoothing methods image edge detection Computational modeling signal processing algorithms Reliability Underwater acoustics image enhancement signal to noise ratio

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Iterative Operator Sketching Framework for Large-Scale Imaging Inverse Problems

Iterative Operator Sketching Framework for Large-Scale Imagi...

引用

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

作者： Junqi Tang Subhadip Mukherjee Carola-Bibiane Schönlieb School of Mathematics University of Birmingham Birmingham UK Department of E&ECE IIT-Kharagpur Kharagpur India DAMTP University of Cambridge Cambridge UK

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Despite impressive empirical performance in various imaging applications, iterative data-driven reconstruction (IDR) schemes such as plug-and-play algorithms and deep unrolling networks can have significant computational limitations, especially for large-scale imaging inverse problems. This is mostly because they need to involve the high-dimensional forward/adjoint operators that are expensive to compute in each iteration. In this work, we propose a new operator sketching framework tailored for designing efficient IDR schemes, which are currently state-of-the-art solutions for imaging inverse problems. Our framework performs dimensionality reduction in both image and measurement data domains, leading to efficient computations. Using this framework, we derive several accelerated IDR schemes, such as the plug-and-play multi-stage sketched gradient (PnP-MS2G) and sketching-based primal-dual (LSPD and Sk-LSPD) deep unrolling networks. Our experiments on x-ray CT image reconstruction demonstrate the remarkable effectiveness of the proposed sketched IDR methods.

关键词： Dimensionality reduction Uncertainty Inverse problems Imaging signal processing algorithms signal processing Computational efficiency Speech processing image reconstruction x-ray imaging

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Efficient Co-Approximate Parallel Compressive Depth Reconstruction on FPGA

Efficient Co-Approximate Parallel Compressive Depth Reconstr...

引用

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

作者： Yun Wu John McAllister School of Electrical Electronic and Computer Engineering Queen’s University Belfast

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Efficient depth image reconstruction from sparse samples is crucial for machine perception applications, such as robotics, vehicle assistance and autonomy. It demands fast processing speed with low power consumption for sensing quality and safety, as well as cost reduction for FPGA and solid state implementations, within constrained resource budgets on edge devices. A new co-approximate framework of parallel approximate compressive depth reconstruction engine on FPGA is proposed using ℓ 1 solvers, proximal gradient decent (PGD), with instrumented frequency and voltage scaling during the iterative optimization process. By evaluating various number of parallel approximate processing units for the depth image reconstruction engine, up to 51% further power saving is achieved, and 421× speed up of parallel processing compared to the baseline, henceforth the efficiency is elevated over 43×.

关键词： image coding Power demand Instruments Voltage Robot sensing systems Throughput Sensors image reconstruction Field programmable gate arrays Engines

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Compressor-Based Approach for Power-Optimized Error-Tolerant High Accurate Approximate Multipliers Design and Implementation

Compressor-Based Approach for Power-Optimized Error-Tolerant...

引用

International conference on signal processing and Communication (ICSC)

作者： Lakshmi Sowjanya Koneru Shravya Manchala Prakash Kodali dept. Electronics and Communication NIT Warangal dept. Electronics and Communication NIT Andhra Pradesh

ISBN: (数字)9798331511890

ISBN: (纸本)9798331511906

A common operation in many different applications is multiplication. The performance of a multiplier can be increased by using compressors. Approximate multipliers fall under Approximate Computing, a developing approach focused on en-hancing power efficiency, reducing area, and minimizing delay in applications that can tolerate acceptable errors. It also trades off the necessity of exact computation for improved performance. By using this approach, power usage can be reduced in applications in which precision is not given much importance. An efficient 8-bit approximate multiplier design is achieved by introducing a approximate compressor. The experimental results demonstrate substantial improvements in an 8-bit multiplier, reducing total power by up to 28.4% versus exact multipliers and 31.71% versus existing designs while decreasing delay by up to 54.93% and 72.15% respectively. The average accuracy is found to be 97.02%. The results not only reduce the power consumption but also maintain acceptable levels of precision, demonstrating that this is an effective solution for modern image processing and signal processing applications. The findings add to what we already know about approximate computing, which is important for future research and development in creating energy-efficient digital systems.

关键词： Accuracy Power demand image coding Approximate computing Compressors Hardware Delays Table lookup Error correction Research and development

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Optimizing Multimodal image Fusion: A Novel Approach with Nystrom Attention Mechanisms in Transformer Models

Optimizing Multimodal Image Fusion: A Novel Approach with Ny...

引用

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

作者： Yuqin Zeng Ze Wen Shuqian Fan Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing China Chongqing School University of Chinese Academy of Sciences Chongqing China Chongqing Key Laboratory of Additive Manufacturing Technology (CIGIT CAS) Chongqing China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

This work proposed a new model based on transformers for multimodal image fusion, with explicit attention paid to fusing infrared and visible images toward enhanced detail and information content. This method, which incorporates Nystrom attention and skip connections, optimizes the fusion process so that important features of both modalities are preserved. Traditional models find it hard to keep details in the content and introduce artifacts. On the contrary, this model can efficiently cope with these challenges, as it makes use of an attention mechanism that is computationally highly effective. This will efficiently fuse large-scale image data and may be useful in those fields where very detailed and comprehensive visual information is demanded. The detailed evaluations prove that our model has superior performance over the current state-of-the-art methods in texture detail preservation, thermal differentiation, and overall image quality, which possesses great potential for advanced imaging applications.

关键词： image quality Visualization Attention mechanisms Fuses Computational modeling Imaging signal processing Transformers Speech processing image fusion

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Identical Human Preference Alignment Paradigm for Text-to-image Models

Identical Human Preference Alignment Paradigm for Text-to-Im...

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

Implicit reward mechanism of Direct Preference Optimization (DPO) has facilitated its recent applications beyond large language models (LLMs), notably in aligning text-to-image models with human preferences. While promising results have been achieved with algorithms such as Diffusion-DPO, their reliance on the assumptions of the Bradley-Terry model could potentially lead to significant overfitting. In this paper, we propose the Step Identical Preference Alignment (SIPA) method, departing text-to-image alignment from the assumptions of Bradley-Terry preference model. We assess the performance of four models, Diffusion-DPO, SPO, and SIPA, alongside the original model, on the HPS-V2 test set, which focus on three key aspects: text-image alignment, human value alignment, and generation diversity. Experimental results show that SIPA matches or outperforms existing SOTA alignment methods, and even exceeds the original model in terms of generation diversity, which compellingly demonstrates SIPA’s superiority in mitigating alignment overfitting.

关键词： Large language models Text to image signal processing algorithms signal processing Acoustics Speech processing Optimization Overfitting

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Generalizable Real-time Accelerated Dynamic MRI

Generalizable Real-time Accelerated Dynamic MRI

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

作者： Silpa Babu Wahidul Alam Rushdi Zahid Rusho Sajan Goud Lingala Namrata Vaswani ECE Dept Iowa State University USA BME Dept University of Iowa USA

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

We introduce a real-time undersampled dynamic MRI algorithm, termed FewShot-AltGDmin-MRI, that is generalizable: works for many different applications and sampling trajectories without any application-specific parameter tuning. FS-AGM-MRI operates in real-time after processing the first short mini-batch, i.e., it can provide a reconstruction of each new image frame as soon as the MRI scan data for that frame arrives. It also provides a second set of improved quality reconstructions after a short delay. We compare our algorithm against many state of the art batch MRI algorithms, including Deep Learning (DL) based ones, on 17 different retrospectively undersampled datasets and two prospective datasets. FS-AGM-MRI is the only approach that provides accurate recovery for all datasets while also being one of the fastest.

关键词： Magnetic resonance imaging Heuristic algorithms signal processing algorithms signal processing Real-time systems Trajectory Delays Speech processing image reconstruction Tuning

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