| About this Abstract |
| Meeting |
TMS Specialty Congress 2025
|
| Symposium
|
Joint Sessions of AIM, ICME, & 3DMS
|
| Presentation Title |
FactoryNet: A Labeled Image Dataset for the Manufacturing Environment |
| Author(s) |
Erick Braham, Andrew Bowman, William Bernstein |
| On-Site Speaker (Planned) |
Erick Braham |
| Abstract Scope |
Human labeled image datasets are essential to training and developing AI models. Most image datasets with high volumes of data contain low specificity of image classes. A public open image dataset focused on the manufacturing environment with a high volume of images in the manufacturing domain would benefit the development of visual AI for manufacturing. The FactoryNet dataset is a growing, high-quality labeled image dataset of in-context images for the manufacturing community. Initial efforts to build the dataset have utilized web scraping, factory scans, and industry collaborations. We present the first iteration of the human labeled dataset, looking at the data sanitization and design choices taken to this point. We look toward the future of this resource and how it is and will continue to be an open resource for the manufacturing community. |
| Proceedings Inclusion? |
Definite: Post-meeting proceedings |