δLTA: Decoupling Camera Sampling from Processing to Avoid Redundant Computations in the Vision Pipeline-Reference-Cited by-同舟云学术

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δLTA: Decoupling Camera Sampling from Processing to Avoid Redundant Computations in the Vision Pipeline

Published:2023-10-28 Issue: Volume: Page:
ISSN:
Container-title:56th Annual IEEE/ACM International Symposium on Microarchitecture
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Author:

Taranco Raúl¹^ORCID,Arnau José-María¹^ORCID,González Antonio¹^ORCID

Affiliation:

1. Universitat Politècnica de Catalunya, Spain

Funder

Catalan Institution for Research and Advanced Studies (ICREA)

Horizon 2020 Framework Programme

Spanish State Research Agency (MCIN/AEI)

Spanish Ministry of Education

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3613424.3614261

Reference92 articles.

1. Cnvlutin: Ineffectual-Neuron-Free Deep Neural Network Computing

2. Low-Power Computer Vision: Status, Challenges, and Opportunities

3. Arm. 2022. Arm Frame Buffer Compression. https://www.arm.com/technologies/graphics-technologies/arm-frame-buffer-compression Arm. 2022. Arm Frame Buffer Compression. https://www.arm.com/technologies/graphics-technologies/arm-frame-buffer-compression

4. Arm. 2023. Mali-C32. https://developer.arm.com/Processors/Mali-C32 Arm. 2023. Mali-C32. https://developer.arm.com/Processors/Mali-C32

5. SURF: Speeded Up Robust Features

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