Complex human eye
By enabling automation of quality inspection
Assist workers in their work.
Existing factories have used machines for simple tasks such as numerical measurement, barcode recognition, and member inspection.
Factory automation system refers to a system that automatically controls automatic warehouses, industrial robots, numerical control machine tools, conveyors, unmanned transport vehicles, and quality inspection devices through the system to improve the working environment of such factories.
Deepnoid's DEEP:FACTORY is a deep learning-based machine vision solution specifically designed for such factory automation. In addition to the simple tasks previously performed by traditional machine vision, deep learning technology helps automate complex inspection tasks previously performed by human eyes.
Inspection application based on deep learning technology
DEEP:FACTORY
Advanced machine vision performance
Using deep learning technology, we are upgrading complex inspection tasks that were previously performed by human eyes, such as defect detection and final assembly verification, through automation.
Save time, increase efficiency
If you set priorities based on the analysis result data, you can reduce the burden of time and improve efficiency in various tasks such as determining whether wafers and atypical objects are good or bad, detecting secondary batteries and fibers, PCB inspection, and automatic detection of texture defects. can be expected.
Rapid response to various kinds of work
Even non-professionals without coding skills can easily connect more than 90 types of preprocessing and advanced neural network modules supported by Deepnoid by drag and drop. ) Able to respond quickly according to trends and types of work.
What DEEP:FACTORY ?
data registration
Register the labeled training data.
Use of artificial intelligence
The verified artificial intelligence (AI) model is used in the field.
artificial intelligence design
Design artificial intelligence (AI) to find the desired defect.
artificial intelligence learning
Using data to design artificial intelligence (AI) models
Train and validate performance.
Sample Cases by Function
Classification
A deep learning tool that labels the learned images to determine whether the image information is acceptable or not.
Segmentation
A deep learning tool that displays the shape and location of defects in image information
Wafer pass/fail judgment
Determination of acceptance or rejection of irregular objects
Secondary battery failure detection
Fiber defect detection
Detection
A deep learning tool that displays the location of any defect and the type of defect in the image information.
PCB inspection
Based Artificial Intelligence (AI) Research
Available Applications
mobile
food
PCB
steel
secondary battery
security
car
distribution
Restrictions
Material