Overview
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:
1. Collect images of "qualified samples" and load them into the system.
2. Train these qualified samples through the system to learn and create a reference model.
3. 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.
AI deep learning system
Deep learning neural network technology has begun to integrate into various markets and has gradually become a basic technology.
Especially in the field of manufacturing, it can teach machines to perform detailed judgments that only humans could do in the past. Simply put, it is "combining artificial intelligence with machine vision."
AI visual deep learning technology imitates human thinking, by imitating the neuron network in the human brain,
Recognize complex images, distinguish trends, find distorted artifacts and hard-to-read characters,
While allowing for natural variation in complex patterns, it combines the specificity and flexibility of human visual inspection.
