+49 (911) 80 10 30

Give us a call or have us call you back!

Simply leave a message with your callback appointment

Your Name *

Your phone number *

Callback date *

Callback time *

Your request *

In order to process your request, it is necessary to process the data you provide. This means that by submitting the contact form, you consent to your data being processed (see Privacy Policy). You can object to the processing of your data at any time.

* All fields marked with an asterisk are mandatory fields.
Send a message

Your Name *

Your email *

Your phone number

Your request *

In order to process your request, it is necessary to process the data you provide. This means that by submitting the contact form, you consent to your data being processed (see Privacy Policy). You can object to the processing of your data at any time.*

* All fields marked with an asterisk are mandatory fields.
Social Media

Share page

AI420: Quality Control in Manufacturing with Image Recognition Models

Training: Artificial Intelligence

Participants learn how to develop and train image recognition models to automatically distinguish defective from non-defective products in manufacturing. They train deep neural networks with TensorFlow and Keras, evaluate performance using test data, and consolidate their knowledge through practice-oriented exercises in quality control.

Appointment selection

Appointments in English language (0)


Unfortunately there are currently no available appointments. Would you like to request an appointment? Then click on 'No matching appointment?'

Possible course languages: German

Request prefered appointment period:

Your Name *

Your email *

Your phone number

Preferred period from *

Preferred period to *

Number of participants *

Your message

* All fields marked with an asterisk are mandatory fields.

Unfortunately there are currently no available appointments.
Would you like to request an appointment? Then click on 'No matching appointment?'

Request prefered appointment period:

Your Name *

Your email *

Your phone number

Preferred period from *

Preferred period to *

Number of participants *

Your message

* All fields marked with an asterisk are mandatory fields.

Agenda:

Data motivation and preprocessing:
- Introduction to quality control challenges in manufacturing, data acquisition and preprocessing for model training

Deep neural networks for image recognition and alternative options for model utilization:
- Fundamentals of deep neural networks, various image recognition models and their applications, selection of appropriate model

Training a neural network with TensorFlow and Keras:
- Introduction to TensorFlow and Keras, creation and training of an image recognition model, optimization of model performance

Model evaluation using test data:
- Methods for evaluating model performance, analysis of results, improvement possibilities and model adjustments

Application of learned concepts to real-world scenarios, discussion of best practices and potential implementation challenges

Objectives:

Learning the application of image recognition for quality control, creation and training of models for product classification, evaluation of model performance.

Target audience:

Developers
IT Professionals

Prerequisites:

AI200 Introduction to Python for Data Science and AI (alternatively basic knowledge in Python)
AI220 Introduction to Machine Learning
AI225 Introduction to Deep Learning and AI

Description:

In the workshop AI420 Quality Control in Manufacturing with Image Recognition Models you will learn how to distinguish defective from non-defective products in manufacturing and how to create and train image recognition models to perform this classification automatically.

Participants learn how to train a deep neural network with TensorFlow and Keras and how to evaluate the model's performance using test data. The course provides both a theoretical foundation and practical exercises to provide participants with the necessary knowledge and skills for effective application of image recognition models in quality control.