Integrated circuit (IC) chips form the backbone of the electronics industry; and like any other high-power industry, component manufacturers are fluid, constantly changing, dividing, and merging ownerships. For this reason, successful IC startups or spinoffs will often have IC components that are still sold and used on modern circuit boards despite the company itself not having a large online presence. Needless to say, this can make tracking down individual components difficult.
Logos
IC components are small. Many of the most popular components (resistors, capacitors, etc.) rarely have manufacturer information. Even the most basic information, like company logos or part numbers can be missing. Even when the part numbers are present, it may be difficult to track down which manufacturer created and sold the part, making part replacement nearly impossible.
Dataset
The dataset collected for this project comprises over 2,000 hand-picked and hand-labeled images spanning more than 60 component manufacturers. Although still growing, the dataset includes companies like Motorola, Acer, Sanyo, Texas Instruments, and many more. Images were collected from mass sales websites like Ebay, Alibaba, and IndianMart, as well as images websites like Google Images, Wikimedia, and TheRetroWeb.
Still unders construction, the model requires each dataset to contain at least 20 images to be considered in its training set. As of writing, the largest manufacturer dataset contains 61 images (Toshiba), while the smallest manufacturer dataset are only 1 image (RCWL).
Transfer Learning Model
The model used for this study compares a variety of transfer learning models, including ResNet, EfficientNet, DenseNet, and others.
Conclusion
Current model accuracy sits around 80%.