Practice

Field project practice

Focus on industrial applications of machine vision. Cover basic digital image processing and application to machine vision and automation fields. Introduce application cases of manufacturing environments and problem solve industrial projects.
Students will solve projects through Neurocle software based on what they have learned.

If your students want to...

- Learn the basic concepts of deep learning.
- Understand the process of creating a deep learning model.
- Understand the basic structure of deep learning networks.

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Smart Factory Project

Product vision inspection automation

Directly build an automated exterior inspection system in the industrial field with deep learning vision technology.

You can inspect the exterior and detect defects of various products such as PCB components, rechargeable batteries, food products, and packaging.

Logistics vision inspection automation

Build logistics automation solutions for warehouses and factories.

Our software recognizes product codes printed on boxes of various sizes and materials, reads part numbers such as manufacturing dates, and checks whether stickers or labels exist.

Autonomous Driving System Project

Signal recognition

Recognize traffic signals by using a classification model that identifies the meaning of an entire image.

By training the images of the three signals, the autonomous vehicle can drive or stop depending on the situation.

Person and object recognition

Detect various objects using the Object Detection model, which is a model that detects the type, location, and number of objects.

Let the car drive while avoiding objects recognized as obstacles based on training results.

Inference Program Development

Intepreter development

With Neurocle Runtime Framework*, you can configure example code environments and run examples for real-time deployment of deep learning models.

*APIs provided by Neurocle (Status, Device, NDBuffer, Shape, Model, Executor)