Algorithm Upgrade | Explore New Skills, KeyeTech Help to Assist in Artificial Intelligent Journey

Technological innovation is the core element for developing new quality productive forces. Continuously strengthening innovation in artificial intelligence technology, and providing a powerful source of power for the production of new quality productive forces with higher technological content of labor materials, KeyeTech has deeply cultivated the field of artificial intelligence of visions defect detection technology, continuously exploring and researching algorithms and computing power. KeyeTech has successfully developed its own AI computing power unit, helping visual inspection take great strides towards acceleration. In 2024, Keye has also made significant breakthroughs in algorithm research for AI visions inspection system field.

Automatic Annotation

In the era of big data, data is undoubtedly a valuable resource. However, how to efficiently and accurately annotate massive amounts of data has become a huge challenge. The traditional manual annotation method is inefficient and has a high error rate. The application of Keye's automatic annotation function is like a timely rain, opening a new door for data annotation.

Automatic annotation is based on deep learning and natural language processing techniques, which can automatically recognize text and image data. With just a simple click of the mouse, sample defects can be accurately identified and annotated. Significantly improved annotation efficiency and quality.

Positive-going Training Mode

Compared to traditional training methods, KEYE places more emphasis on precise data screening and strict quality control. Only selecting positive samples that meet the requirements for training avoids the interference of incorrect and unexpected data on model training, thereby improving the accuracy and reliability of the model.

The core of positive-going sample training lies in its ability to accurately recognize and output correct training results through learning from good samples, greatly improving recognition ability and data output accuracy for appearance defect inspection industry.