Bridging Latency and Accuracy: FPGA-Based Deep Learning Pipelines for Real-Time Closed-Loop Neural Decoding

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-30
DOI
https://doi.org/10.5281/zenodo.17236636
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
Field-Weighted Citation Impact
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article

Bridging Latency and Accuracy: FPGA-Based Deep Learning Pipelines for Real-Time Closed-Loop Neural Decoding

Zenodo (CERN European Organization for Nuclear Research)
Adversarial Robustness in Machine Learning
article

Bridging Latency and Accuracy: FPGA-Based Deep Learning Pipelines for Real-Time Closed-Loop Neural Decoding

article en

Abstract

No abstract available for this paper.
Zenodo (CERN European Organization for Nuclear Research)
University of Sheffield (GB)
Industry, innovation and infrastructure
Openalex Percentile: Top 25%
Adversarial Robustness in Machine Learning
DOIOpen Access PDFOpenAlex
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Bridging Latency and Accuracy: FPGA-Based Deep Learning Pipelines for Real-Time Closed-Loop Neural Decoding · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS