Sensors · 2022 publication
Collaborative Edge-Cloud Face Recognition
Research co-author
Published research into face-recognition inference across edge and cloud systems.
영문 기술 설명
문제
Improve face-recognition inference performance by using edge and cloud computing collaboratively.
담당 업무
- Co-author “Optimizing face recognition inference with a collaborative edge–cloud network.”
- Contribute to research on distributed face-recognition inference.
기술적 접근
The research investigates collaborative edge–cloud inference rather than treating device and cloud processing as isolated alternatives. The linked paper is the source for the experimental method and reported results.
Research question
Investigate collaborative face-recognition inference across edge and cloud computing.
Engineering considerations
Account for the relationship between device computation and network communication when interpreting inference performance.
Reproducible evidence
Consult the linked Sensors paper for the experimental setup and results. The published work is a team contribution.
설계 시 고려사항
Inference placement introduces a balance between device computation and network communication. Hardware and network conditions matter when interpreting throughput or latency results.
결과
Peer-reviewed publication in Sensors, volume 22, issue 21, article 8371 (2022).
근거 및 범위
Read the linked paper for experimental conditions and measurements. Results are team research; this page does not attribute every component to an individual contributor.