ZenoVision Defect detection system

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ZenoVision Defect detection system

ZenoSensor Online Thickness Gauge Product Series

Automatic adjustment of mold head closed-loop control system

Intelligent Comma Scratching Equipment

Zenovision Diagram of defect detection process and principle

Main components and design principles

Rigorous quality control system and excellent reliability
24/7 comprehensive technical support services
Green environmental protection concept and sustainable development strategy
Industry certified standardized LED light source system
Automated Feature Learning and Self Iterative Optimization Based on Deep Learning
Innovative modular design and convenient scalability
High quality standard industrial cameras and precision optical lenses
Excellent Performance Industrial Standard Image Processing Unit
Personalized industrial software solutions for customization

Intelligent and efficient detection system driven by the fourth generation deep learning GPU

1

Fourth generation deep learning GPU

CPU+GPU dual threaded processing architecture, with simultaneous multi-threaded processing. Easily handle high-precision and high-speed data

2

More precise detection

Using artificial intelligence for autonomous learning to extract defect features and minimize human intervention

3

More accurate classification

Built in billions of defect samples, deep learning AI detection defect classification, covering surface defect expert knowledge base, can quickly deploy the system
4

Have a swift response

Detection and classification can quickly respond to high-speed production lines

5

Diverse algorithms

More than 18 algorithms; Multidimensional defect classification methods; Multi threading for AI defect recognition

6

Secondary learning

Collect production line data after installation and operation, perform a second precise classification, and optimize the classification based on on-site process optimization