FedTR: Federated Learning Framework with Transfer Learning for Industrial Visual Inspection-Reference-Cited by-同舟云学术

FedTR: Federated Learning Framework with Transfer Learning for Industrial Visual Inspection

Published:2024-06-12 Issue: Volume: Page:310-314
ISSN:
Container-title:Proceedings of the Great Lakes Symposium on VLSI 2024
language:
Short-container-title:

Author:

Sathiamoorthy Vikash¹^ORCID,Huai Shuo²^ORCID,Kong Hao¹^ORCID,Liu Di³^ORCID,Loy Wendy Yong Yi¹^ORCID,Makaya Christian⁴^ORCID,Ho Daren⁵^ORCID,Subramaniam Ravi⁴^ORCID,Lin Qian⁴^ORCID,Liu Weichen¹^ORCID

Affiliation:

1. Nanyang Technological University, Singapore

2. School of Computer Science and Engineering, Nanyang Technological University, Singapore

3. Norwegian University of Science and Technology, Norway

4. HP Inc., USA

5. HP Singapore, Singapore

Funder

the RIE2020 Industry Alignment Fund ? Industry Collaboration Projects (IAF-ICP) Funding Initiative

Academic Research Fund Tier 1 (RG94/23) Singapore; NAP Nanyang Technological University

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3649476.3658768

Reference13 articles.

1. What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis

2. The Singapore Personal Data Protection Act and an assessment of future trends in data privacy reform

3. Hee-Jae Cho and Vladimir Pucik. 2005. Relationship between innovativeness, quality, growth, profitability, and market value. Strategic management journal 26, 6 (2005), 555–575.

4. Ankush Gupta 2016. Synthetic Data for Text Localisation in Natural Images. In IEEE Conference on Computer Vision and Pattern Recognition.

5. Shuo Huai 2022. Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems. In 2022 IEEE 40th International Conference on Computer Design (ICCD). IEEE, 627–634.