Machine Vision Inspection
Mechanical Features
Using visual sensing equipment (industrial cameras) with image recognition software for subtractive detection, Through the detection assistance of machine vision, the subtle defects on the product are screened out and eliminated. According to the difference in product characteristics and test results, Plan a suitable visual elimination import process to greatly reduce the outflow rate of defective products.
How to train and operate AI machine vision?
There is no need for cumbersome software writing. The built-in algorithm can be trained through a set of samples and its reference model can be created. The training steps only need to perform the following three steps:
- Collect images of "qualified samples" and load them into the system.
- Train these qualified samples through the system to learn and create a reference model.
- Continue testing and fine-tuning, and start detecting anomalies.
Defective areas can be quickly identified and analyzed while understanding the natural variation in sample appearance, and most importantly, training without large numbers of defective samples.
Model AI deep learning & CCD
AI Deep Learning System
Deep learning neural network technology has begun to integrate into various markets and is gradually becoming a foundational technology. In the manufacturing sector in particular, it enables machines to perform fine judgments that were previously only possible for humans. Simply put, it is the integration of artificial intelligence with machine vision.
AI-based visual deep learning technology mimics human thinking by modeling neural networks similar to those in the human brain. It can recognize complex images, distinguish patterns and trends, identify deformed workpieces and hard-to-read characters, while allowing natural variations in complex patterns, combining the specificity and flexibility of human visual inspection.
