Umeå University's logo

umu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Edge-AI-driven framework with efficient mobile network design for facial expression recognition
Hohai University, Jiangsu Province, Nanjing City, China.
Hohai University, Jiangsu Province, Nanjing City, China.
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.ORCID iD: 0000-0003-4228-2774
Jiangsu University, Jiangsu Province, Zhenjiang City, China.
Show others and affiliations
2023 (English)In: ACM Transactions on Embedded Computing Systems, ISSN 1539-9087, E-ISSN 1558-3465, Vol. 22, no 3, article id 57Article in journal (Refereed) Published
Abstract [en]

Facial Expression Recognition (FER) in the wild poses significant challenges due to realistic occlusions, illumination, scale, and head pose variations of the facial images. In this article, we propose an Edge-AI-driven framework for FER. On the algorithms aspect, we propose two attention modules, Arbitrary-oriented Spatial Pooling (ASP) and Scalable Frequency Pooling (SFP), for effective feature extraction to improve classification accuracy. On the systems aspect, we propose an edge-cloud joint inference architecture for FER to achieve low-latency inference, consisting of a lightweight backbone network running on the edge device, and two optional attention modules partially offloaded to the cloud. Performance evaluation demonstrates that our approach achieves a good balance between classification accuracy and inference latency.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2023. Vol. 22, no 3, article id 57
Keywords [en]
cloud offloading, Deep learning, edge computing, Facial Expression Recognition
National Category
Computer Systems Computer Sciences
Identifiers
URN: urn:nbn:se:umu:diva-212242DOI: 10.1145/3587038Scopus ID: 2-s2.0-85164280960OAI: oai:DiVA.org:umu-212242DiVA, id: diva2:1783359
Funder
The Kempe FoundationsAvailable from: 2023-07-20 Created: 2023-07-20 Last updated: 2023-07-20Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Gu, Zonghua

Search in DiVA

By author/editor
Gu, Zonghua
By organisation
Department of Applied Physics and Electronics
In the same journal
ACM Transactions on Embedded Computing Systems
Computer SystemsComputer Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 91 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf