Scenario Application - Challenges and Solutions in the Sorting of Metal Materials
Date:2026-03-07 Views:1
Metal materials have complex compositions and diverse forms. Traditional manual sorting methods are inefficient and have a high error rate, making it difficult to meet the requirements of modern industry for sorting accuracy and processing capacity. In the actual sorting process, metal surfaces are generally subject to complex states such as oxidation, rust, oil stains, and scratches. Coupled with significant size differences and irregular shapes of materials, it is easy to cause identification blind spots or false triggers, increasing the difficulty of sorting.
The AI crawler sorter from Keyi Technology provides an optimal solution for metal sorting through advanced visual imaging and AI algorithms.
- The use of a high-dimensional HDR camera (pro) enables the capture of images with distortion correction through optical design and algorithm models, accurately capturing material features in motion shooting mode, resulting in clearer imaging.
2. Customized light source system: Different from the RGB light sources of other devices on the market, Keyi Technology adopts customized light sources that can more clearly reproduce the natural appearance of the detected objects, breaking through the limitations of traditional light sources and reducing false positives and false negatives.
3. Deep learning AI algorithm, with precise accuracy. By extracting material features, comparing and learning, and judging materials, rapid modeling can be achieved within 1 hour. Combined with Keyi Technology's self-developed cloud platform, a vast array of algorithm models are available online to meet sorting standards for different scenarios and application needs.
