" What if a machine learn by experience? "
R&D team of Pixel targets on integrating Artificial Intelligence technology with machine vision to automate currently require extensive manual labor.
Using Artificial intelligence, specifically Deep Learning technology, we can replace static image processing algorithms with pre-trained neural networks, to perform the inspection operation
Traditionally Inspection systems are used fixed algorithms to detect defect, but the limitation is which detect only fixed defects. If any new defect type comes we should create new algorithm for it. And need of extensive human labor to verify false alarms. Thous our R&D team integrating DEEP LEARNING with existing automated inspection system
Benefits of using DEEP LEARNING
> Continuously trained for new defects without the need of change in Algorithm
> Sensitivity can be controlled by adjusting the level of training.
> False alarms can be reduced without the help of human by proper training.
To implement, need to consider the following steps
> Classify images for training.
> Feed the classified images to our system and start training.
> The system automatically trains itself based on the given images.
> Export the neural network to our inspection system