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http://bura.brunel.ac.uk/handle/2438/23048Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Ammatmanee, C | - |
| dc.contributor.author | Gan, L | - |
| dc.contributor.author | Liu, H | - |
| dc.date.accessioned | 2021-08-03T16:55:44Z | - |
| dc.date.available | 2021-07-05 | - |
| dc.date.available | 2021-08-03T16:55:44Z | - |
| dc.date.issued | 2021-06-09 | - |
| dc.identifier.citation | Ammatmanee, C., Gan, L. and Liu, H. (2021) 'Fast Binary Embedding of Deep Learning Image Features Using Golay-Hadamard Matrices,' in 2021 IEEE International Conference on Multimedia and Expo (ICME). Shenzhen, China, 5-9 July, pp. 1-6. doi: 10.1109/ICME51207.2021.9428130. | en_US |
| dc.identifier.isbn | 978-1-6654-3864-3 | - |
| dc.identifier.isbn | 978-1-6654-1152-3 | - |
| dc.identifier.issn | 1945-7871 | - |
| dc.identifier.issn | 1945-788X | - |
| dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/23048 | - |
| dc.format.medium | Print-Electronic | - |
| dc.language.iso | en_US | en_US |
| dc.publisher | IEEE | en_US |
| dc.rights | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | - |
| dc.source | 2021 IEEE International Conference on Multimedia and Expo (ICME) | - |
| dc.source | 2021 IEEE International Conference on Multimedia and Expo (ICME) | - |
| dc.subject | convolutional neural network | en_US |
| dc.subject | deep learning | en_US |
| dc.subject | structured matrix | en_US |
| dc.subject | binary embedding | en_US |
| dc.subject | Hadamard matrix | en_US |
| dc.subject | Golay sequence | en_US |
| dc.subject | dimensionality reduction | en_US |
| dc.title | Fast Binary Embedding of Deep Learning Image Features Using Golay-Hadamard Matrices | en_US |
| dc.type | Conference Paper | en_US |
| dc.identifier.doi | https://doi.org/10.1109/icme51207.2021.9428130 | - |
| dc.relation.isPartOf | 2021 IEEE International Conference on Multimedia and Expo (ICME) | - |
| pubs.finish-date | 2021-07-09 | - |
| pubs.finish-date | 2021-07-09 | - |
| pubs.publication-status | Published | - |
| pubs.start-date | 2021-07-05 | - |
| pubs.start-date | 2021-07-05 | - |
| Appears in Collections: | Dept of Electronic and Electrical Engineering Research Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | 470.76 kB | Adobe PDF | View/Open |
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