Name
Abstract | ||
|---|---|---|
Online and cloud storage has become an increasingly popular location to store personal data that led to raising the concerns about storage and retrieval. Similarity-preserving hashing techniques were used for fast storing and retrieval of data. In this paper, a new technique is proposed that uses both randomizing and hashing techniques in a joint structure. The proposed structure uses a Siamese-Twin architecture neural network that applies random projection on data before being used. Furthermore, Particle Swarm Optimization and Genetic Algorithms are used to fine-tune the Siamese-Twin neural network. The proposed technique produces a compact binary code with better retrieval performance than other hashing randomizing technique that varies from 2 % to 5 %. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-48308-5_38 | PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT SYSTEMS AND INFORMATICS 2016 |
Keywords | DocType | Volume |
Neural network,Genetic algorithms,Similarity preserving hashing,Random projection | Conference | 533 |
ISSN | Citations | PageRank |
2194-5357 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohamed Moheeb Emara | 1 | 0 | 1.01 |
| Mohamed Waleed Fahkr | 2 | 0 | 0.34 |
| M. B. AbdelHalim | 3 | 45 | 7.21 |