Research on federal learning techniques for target detection in industrial field images

Yunbo Zhang; Fangjie Wan; Huawei Song

doi:10.1117/12.3026522

27 March 2024 Research on federal learning techniques for target detection in industrial field images

Yunbo Zhang, Fangjie Wan, Huawei Song

Proceedings Volume 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023); 131053W (2024) https://doi.org/10.1117/12.3026522
Event: 3rd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 2023, Qingdao, China

Abstract

In the age of data and information, the amount of data is increasing and the privacy protection of data is becoming more and more important. Federated learning model is a distributed deep learning model that can aggregate model parameters from multiple clients while protecting private data. For the scenario of an industrial site where each factory cannot share its private data, the federated learning model allows each local factory to train its own model based on its own data, and then upload the model to a central server for continuous iteration and training. However, because the quantity and quality of data varies from one client to another, this can have an impact on the accuracy of the model. In order to reduce the above impact, an optimisation method that adds a weighted adjustment processing to the model on top of the federated learning model (FedAvg) is proposed. The final experimental results illustrate that the model obtained from the training of this optimisation method has better accuracy compared to the traditional federated learning model.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yunbo Zhang, Fangjie Wan, and Huawei Song "Research on federal learning techniques for target detection in industrial field images", Proc. SPIE 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 131053W (27 March 2024); https://doi.org/10.1117/12.3026522

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KEYWORDS

Data modeling

Target detection

Education and training

Machine learning

Object detection

Computer security

Data transmission

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