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Deep Learning

Advantages of Deep Learning

Advantages of Deep Learning

Deep learning expands the limits of what a computer and camera can inspect

Deep learning has turned applications that previously required vision expertise into engineering challenges solvable by non-vision experts. Deep learning transfers the logical burden from an application developer, who develops and scripts a rules-based algorithm, to an engineer training the system. It also opens a new range of possibilities to solve applications that have never been attempted without a human inspector. In this way, deep learning makes machine vision easier to work with, while expanding the limits of what a computer and camera can accurately inspect.

Human icon Compared to Human Visual Inspection Machine vision icon Compared to Traditional Machine Vision Open source icon Compared to Deep Learning Open Source Libraries

More consistent

Operates 24x7 and maintains the same level of quality on every line, every shift and every factory. 

Designed for hard-to-solve applications

Solves complex inspection, classification and location applications impossible or difficult with classic rules-based algorithms.

Requires less data and computing power

Training requires hundreds of images instead of millions. Since images are stored locally and require minimal computing resources deployment is fast and affordable.

More reliable

Identifies every defect outside of the set tolerance.

Easier to configure

 Applications can be set up quickly, speeding up proof of concept and development.

Simple training interface 

Software is designed for real-world factory conditions, with no special expertise required.

Faster

Identifies defects in milliseconds, supporting high-speed applications and improving throughput.

Tolerates variations

Handles defect variations for applications that require an appreciation of acceptable deviations from the control.

Global support

Cognex’s network of engineers and technical experts provide world-class application support. 

Human inspectors are skilled at learning by example and appreciating acceptable deviations from the control. Machine vision, by contrast, is much more robust. Deep learning combines the flexibility of human visual inspection with the consistency and speed of a computer.

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