Deep Learning for Industrial Imaging

Education facts

Code: DVA476

This course will teach you how to build convolutional neural networks. You will learn to design intelligent systems using deep learning for classification, annotation, and object recognition. About this course Lesson 1 - Image processing: Introduction of industrial imaging through big data and fundamentals of image processing techniques. Lesson 2 - Deep learning with convolutional neural network: Overview of neural network as classifiers, introduction of convolutional neural network and Deep learning architecture. Lesson 3 - Deep learning tools: Implementation of Deep learning for Image classification and object recognition, e.g. using Keras. What you will learn * Understand the fundamental theory of image processing. * Able to describe the fundamental needs, challenges and limitations of Big data with industrial imaging. * Able to describe and understand the basic principles of convolution neural network. * Demonstrate the ability to use tools for deep learning in industrial imaging

Entry requirements

90 credits of which at least 60 credits in Computer Science or equivalent, including at least 15 credits in programming. In addition, Swedish course B/Swedish course 3 and English course A/English course 6 are required. For courses given entirely in English exemption is made from the requirement in Swedish course B/Swedish course 3.

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

• Deep Learning for Industrial Imaging

  Mälardalen University

  Start date: 13 October 2025

  End date: 30 November 2025

  Pace of study: 25 %