End-to-End Learning Framework Incorporating Image Reconstruction and Recognition Models

End-to-End Learning Framework Incorporating Image Reconstruction and Recognition Models

Edge computing-based image recognition applications face significant challenges, including increased latency and network load when transmitting large volumes of images to edge servers. To address these issues, this study proposes a novel solution that involves sending compressed data from a front-en...

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Bibliographic Details
Main Authors: Ren Shibata, Yuji Yamauchi
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Edge computing
end-to-end learning
image compression
image recognition
Online Access:https://ieeexplore.ieee.org/document/10974964/
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https://ieeexplore.ieee.org/document/10974964/

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