Efficient parallel optimizations of a high-performance SIFT on GPUs-Reference-Cited by-同舟云学术

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Efficient parallel optimizations of a high-performance SIFT on GPUs

Published:2019-02 Issue: Volume:124 Page:78-91
ISSN:0743-7315
Container-title:Journal of Parallel and Distributed Computing
language:en
Short-container-title:Journal of Parallel and Distributed Computing

Author:

Li Zhihao^ORCID,Jia Haipeng,Zhang Yunquan,Liu Shice,Li Shigang,Wang Xiao,Zhang Hao

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Key Technology Research and Development Programs of Guangdong Province

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture,Theoretical Computer Science,Software

Reference43 articles.

1. Speeding up SIFT using GPU;Acharya,2013

2. A real-time implementation of sift using gpu;Acharya;J. Real-time Image Process.,2014

3. Surf: speeded up robust features;Bay,2006

4. M. Björkman, CudaSift: The fourth version of a sift implementation using cuda for gpus, 2017. https://github.com/Celebrandil/CudaSift.

5. Detecting, segmenting and tracking unknown objects using multi-label mrf inference;Björkman;Comput. Vis. Image Underst.,2014

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