GLDH: Toward more efficient global low-density locality-sensitive hashing for high dimensions-Reference-Cited by-同舟云学术

GLDH: Toward more efficient global low-density locality-sensitive hashing for high dimensions

Published:2020-09 Issue: Volume:533 Page:43-59
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Li Yiqi,Xiao Ruliang^ORCID,Wei Xin,Liu Huakun,Zhang Shi,Du Xin^ORCID

Funder

National Natural Science Foundation of China

Fujian Province Science and Technology Plan

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference45 articles.

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