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Computer Science > Computer Vision and Pattern Recognition

arXiv:1810.05730 (cs)
[Submitted on 10 Oct 2018]

Title:CRH: A Simple Benchmark Approach to Continuous Hashing

Authors:Miao Cheng, Ah Chung Tsoi
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Abstract:In recent years, the distinctive advancement of handling huge data promotes the evolution of ubiquitous computing and analysis technologies. With the constantly upward system burden and computational complexity, adaptive coding has been a fascinating topic for pattern analysis, with outstanding performance. In this work, a continuous hashing method, termed continuous random hashing (CRH), is proposed to encode sequential data stream, while ignorance of previously hashing knowledge is possible. Instead, a random selection idea is adopted to adaptively approximate the differential encoding patterns of data stream, e.g., streaming media, and iteration is avoided for stepwise learning. Experimental results demonstrate our method is able to provide outstanding performance, as a benchmark approach to continuous hashing.
Comments: 6 pages
Subjects: Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG)
Cite as: arXiv:1810.05730 [cs.CV]
  (or arXiv:1810.05730v1 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.1810.05730
Related DOI: https://doi.org/10.1109/GlobalSIP.2015.7418363

Submission history

From: Miao Cheng [view email]
[v1] Wed, 10 Oct 2018 14:18:00 UTC (2,153 KB)
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