Publication:
Deep Learning with FPGA: Age and Gender Recognition for Smart Advertisement Board
Deep Learning with FPGA: Age and Gender Recognition for Smart Advertisement Board
| cris.author.scopus-author-id | 58705850100 | |
| cris.author.scopus-author-id | 55193708600 | |
| cris.author.scopus-author-id | 56019340000 | |
| cris.author.scopus-author-id | 58902890800 | |
| cris.author.scopus-author-id | 37005452000 | |
| cris.author.scopus-author-id | 36344007400 | |
| cris.virtual.department | Universiti Malaysia Perlis | |
| cris.virtual.department | Universiti Malaysia Perlis | |
| cris.virtual.department | Universiti Malaysia Perlis | |
| cris.virtualsource.department | 325aae8b-6e9c-40ec-b8c4-398c4b0f1803 | |
| cris.virtualsource.department | d8ff0723-bbe6-45fe-91f3-32aff5d527ab | |
| cris.virtualsource.department | fb026ced-1541-4a65-afa6-3a85059c5273 | |
| dc.contributor.author | Yeoh W.S. | |
| dc.contributor.author | Fazrul Faiz Zakaria | |
| dc.contributor.author | Mustapa M. | |
| dc.contributor.author | Mohd Nazri Mohd Warip | |
| dc.contributor.author | Phak Len Al Eh Kan | |
| dc.contributor.author | Mozi A.M. | |
| dc.date.accessioned | 2024-09-27T08:30:24Z | |
| dc.date.available | 2024-09-27T08:30:24Z | |
| dc.date.issued | 2023-10-06 | |
| dc.description.abstract | Age and gender recognition are helpful in various applications, especially in the field of advertising. To replace the traditional advertising method that can only display the same contents to all audiences, a smart advertisement board capable of detecting age and gender of audiences to display relevant contents is required to increase the effectiveness of advertising. This paper will use two image datasets to train and test the Convolutional Neural Network (CNN) based architecture models for age and gender recognition using deep learning. The dataset that produced the best performing model will be implemented on three different devices to observe the performance of the models on each device. A gender recognition model with accuracy of 91.53% and age recognition model with accuracy of 59.62% is produced. The results have also shown the use of Field Programmable Gated Array (FPGA) has greatly boosted the performance of the models in terms of throughput and latency. | |
| dc.identifier.doi | 10.1063/5.0112167 | |
| dc.identifier.scopus | 2-s2.0-85177561147 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14170/4816 | |
| dc.relation.funding | Ministry of Higher Education, Malaysia | |
| dc.relation.grantno | FRGS/1/2018/ICT03/UNIMAP/02/3 | |
| dc.relation.ispartof | AIP Conference Proceedings | |
| dc.relation.ispartofseries | AIP Conference Proceedings | |
| dc.relation.issn | 0094243X | |
| dc.title | Deep Learning with FPGA: Age and Gender Recognition for Smart Advertisement Board | |
| dc.type | Conference Proceeding | |
| dspace.entity.type | Publication | |
| oaire.citation.issue | 1 | |
| oaire.citation.volume | 2579 | |
| oairecerif.affiliation.orgunit | Universiti Malaysia Perlis | |
| oairecerif.affiliation.orgunit | Universiti Malaysia Perlis | |
| oairecerif.affiliation.orgunit | Universiti Malaysia Perlis | |
| oairecerif.affiliation.orgunit | Universiti Malaysia Perlis | |
| oairecerif.affiliation.orgunit | Universiti Malaysia Perlis | |
| oairecerif.affiliation.orgunit | Universiti Teknologi MARA | |
| oairecerif.author.affiliation | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| oairecerif.author.affiliation | Universiti Malaysia Perlis | |
| oairecerif.author.affiliation | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| oairecerif.author.affiliation | Universiti Malaysia Perlis | |
| oairecerif.author.affiliation | Universiti Malaysia Perlis | |
| oairecerif.author.affiliation | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| oairecerif.citation.number | 020042 | |
| person.identifier.orcid | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| person.identifier.orcid | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| person.identifier.orcid | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| person.identifier.orcid | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| person.identifier.orcid | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| person.identifier.orcid | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| person.identifier.scopus-author-id | 58705850100 | |
| person.identifier.scopus-author-id | 55193708600 | |
| person.identifier.scopus-author-id | 56019340000 | |
| person.identifier.scopus-author-id | 58902890800 | |
| person.identifier.scopus-author-id | 37005452000 | |
| person.identifier.scopus-author-id | 36344007400 |
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