標題: Titlebook: Design and Architectures for Signal and Image Processing; 17th International W Tiago Dias,Paola Busia Conference proceedings 2024 The Edito [打印本頁] 作者: Philanthropist 時間: 2025-3-21 19:46
書目名稱Design and Architectures for Signal and Image Processing影響因子(影響力)
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書目名稱Design and Architectures for Signal and Image Processing被引頻次
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書目名稱Design and Architectures for Signal and Image Processing讀者反饋學(xué)科排名
作者: sed-rate 時間: 2025-3-21 20:49 作者: Asseverate 時間: 2025-3-22 03:32
Design and Architectures for Signal and Image Processing978-3-031-62874-0Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Receive 時間: 2025-3-22 06:10 作者: 空洞 時間: 2025-3-22 09:56
hy (PPG) is one of these trends since PPG sensors are embedded into many devices like smartwatches or oximeters. Due to the versatility of PPG, it is the technique of choice for the non-invasive monitoring of vital signs such as heart rate, respiratory rate, blood oxygen saturation and blood pressur作者: phase-2-enzyme 時間: 2025-3-22 16:28 作者: phase-2-enzyme 時間: 2025-3-22 19:38 作者: extinct 時間: 2025-3-22 23:14
ions. In particular, they have caused a large increase in memory, execution time, and power needed. One solution to address those challenges is to reduce data sizes. Custom floating-point is a good candidate that brings a large dynamic range in a compact representation. Thanks to improvement in floa作者: 競選運動 時間: 2025-3-23 04:41
nas drastically increases the cost of processing and storing their data, complicating the design of computing hardware. Our overall goal is to provide a system, which we term SimSDP, to aid in their design. It will achieve this by providing resource usage estimations for some given imaging pipeline 作者: 尊嚴 時間: 2025-3-23 08:06
y, selecting appropriate computing platforms for these applications is done manually through prototyping and benchmarking. To simplify this selection process, Dataflow (DF) modeling has been utilized to identify opportunities for parallelism. This approach utilizes the Algorithm Architecture “Adequa作者: Jocose 時間: 2025-3-23 11:27
https://doi.org/10.1007/978-1-349-17076-0lication domains such as security, multimedia, signal processing, and machine learning. The efficiency of a CGRA is determined by its architectural features and the compiler’s ability to exploit the spatio-temporal configuration. Numerous design optimizations and mapping techniques have been introdu作者: 無動于衷 時間: 2025-3-23 17:03 作者: 踉蹌 時間: 2025-3-23 20:19 作者: 分開如此和諧 時間: 2025-3-24 01:16
s. The run time of the optimization process is shown to be improved significantly compared to a CPU implementation. With four parallel model execution units, the design runs in about 1.5% of the time required for an Intel Xeon W-1250 CPU. This shows that DP-based optimal control is feasible for HEVs and that FPGAs can be used to achieve it.作者: 故意釣到白楊 時間: 2025-3-24 05:06 作者: 敘述 時間: 2025-3-24 08:26
Conference proceedings 2024024, held in Munich, Germany, during January 17–19, 2024...The 9 full papers presented in this book were carefully reviewed and selected from 21 submissions.?The workshop provided an inspiring international forum for the latest innovations and developments in the fields of leading signal, image, and作者: 不在灌木叢中 時間: 2025-3-24 12:26 作者: contrast-medium 時間: 2025-3-24 18:16 作者: Palter 時間: 2025-3-24 21:03 作者: Morbid 時間: 2025-3-24 23:20
optimize the exponent and mantissa wordlengths. These strategies take advantages of analyzing the data dynamic range to reduce the optimization time. The obtained results show that better implementation cost can be obtained compared to 16-bit floating-point for a same quality.作者: refraction 時間: 2025-3-25 05:59
timate the scaling across both algorithmic parameters as well as parallelization when compared to measured data, with errors roughly in the 1–5% range, demonstrating its ability to inform design decisions.作者: 光亮 時間: 2025-3-25 08:18
Wordlength Optimization for?Custom Floating-Point Systemsoptimize the exponent and mantissa wordlengths. These strategies take advantages of analyzing the data dynamic range to reduce the optimization time. The obtained results show that better implementation cost can be obtained compared to 16-bit floating-point for a same quality.作者: archetype 時間: 2025-3-25 14:26 作者: esthetician 時間: 2025-3-25 17:10
sEMG-Based Gesture Recognition with?Spiking Neural Networks on?Low-Power FPGAer applications. Evaluation on the NinaPro DB5 dataset confirms an accuracy of 85.6%, demonstrating the model’s effectiveness. The power consumption for this architecture is approximately 1.7 mW, leveraging the inherent energy efficiency of SNNs for low-power classification.作者: vocation 時間: 2025-3-25 21:54 作者: 前奏曲 時間: 2025-3-26 01:25 作者: nullify 時間: 2025-3-26 04:53
sEMG-Based Gesture Recognition with?Spiking Neural Networks on?Low-Power FPGAplex prosthetic devices and human-machine interfaces. This study presents a real-time sEMG classification system, exploiting a Spiking Neural Network (SNN) to distinguish among twelve distinct hand gestures. The system is implemented on a Lattice iCE40-UltraPlus FPGA, explicitly designed for low-pow作者: 邪惡的你 時間: 2025-3-26 12:24
Scalable FPGA Implementation of?Dynamic Programming for?Optimal Control of?Hybrid Electrical Vehicleany of these computations can be performed in parallel, FPGAs are an interesting platform for executing the dynamic programming algorithm. This paper presents a scalable architecture for performing dynamic programming on FPGAs using a pipelined model of a hybrid electric vehicle (HEV). The proposed 作者: 無法取消 時間: 2025-3-26 12:41
Wordlength Optimization for?Custom Floating-Point Systemsions. In particular, they have caused a large increase in memory, execution time, and power needed. One solution to address those challenges is to reduce data sizes. Custom floating-point is a good candidate that brings a large dynamic range in a compact representation. Thanks to improvement in floa作者: 集合 時間: 2025-3-26 17:50 作者: Haphazard 時間: 2025-3-26 22:19 作者: LOPE 時間: 2025-3-27 02:58 作者: acrimony 時間: 2025-3-27 07:12
Improving the?Energy Efficiency of?CNN Inference on?FPGA Using Partial Reconfigurationnced solutions for the deployment of highly energy-efficient implementations. This paper presents a novel approach to improve the efficiency of CNN inference on Field-Programmable Gate Arrays (FPGAs) using Partial Reconfiguration (PR). Our method deconstructs CNN topology into different layers for r作者: Offstage 時間: 2025-3-27 12:32
Optimising Graph Representation for?Hardware Implementation of?Graph Convolutional Networks for?Evenst proposals in this area are Graph Convolutional Networks (GCNs), which allow to process events in its original sparse form while maintaining high detection and classification performance. In this paper, we present the hardware implementation of a?graph generation process from an event camera data 作者: 積習(xí)難改 時間: 2025-3-27 15:09 作者: 平項山 時間: 2025-3-27 18:46
Scratchy: A Class of?Adaptable Architectures with?Software-Managed Communication for?Edge Streaming s different topology options and is demonstrated using a 3-core Scratchy. The capabilities of the architecture are presented through a design space exploration that focuses on optimizing the topology for specific applications. It also highlights the low resource overhead of the architecture and quic作者: Gourmet 時間: 2025-3-28 00:20 作者: Pelago 時間: 2025-3-28 06:08
Improving the?Energy Efficiency of?CNN Inference on?FPGA Using Partial Reconfigurationic hardware implementations, respectively. These results also show that the benefits of PR improve with the depth of the network, suggesting very promising levels of gains as the network gets larger and under the key conditions of using fast optimized reconfiguration controllers and methodical syste作者: Influx 時間: 2025-3-28 09:03 作者: 思想 時間: 2025-3-28 10:54 作者: 等待 時間: 2025-3-28 16:33 作者: 抗體 時間: 2025-3-28 19:12 作者: 不理會 時間: 2025-3-29 01:49
