Keye AI algorithm is a vision system solution independently developed by the USTC doctoral team, which has the advantages of few training samples, low annotation volume, strong compatibility, fast operation and deployment speed, etc. At the same time, we have added forward training models according to different scenarios, which is suitable for use in scenarios with high product consistency and fixed detection requirements. That is what we call the forward and reverse AI dual training model.

Technical advantages:
1. Accuracy of results: Compared with traditional visual algorithms, deep learning algorithms have greatly improved stability and can adapt to general disturbances in the environment and background. At the same time, the accuracy of the algorithm is also higher than traditional algorithms;
2. Algorithm universality: For different defects, only their samples need to be collected, and after sufficient training, different defect samples can be automatically identified through deep learning, meeting the needs of large-scale training samples for deep learning. Theoretically, there is no upper limit requirement for the types of defects that can be detected;
3. Development timeliness: As there is no need to develop algorithms for different defects, the entire development cycle is greatly shortened, and creating a new model only takes about 15 minutes at the fastest;
4. Environmental reliability: Due to the guaranteed computing power of NPU, the entire system operates in a state with sufficient computing power margin, and can work for a long time in high temperature environments without easily crashing..