Flanders Make

Operator Actions Recognition using Deep Learning

Flanders Make

Flanders Make is the strategic research centre for the manufacturing industry. Our mission is to strengthen the long-term international competitiveness of the Flemish manufacturing industry. That’s why we work together with SMEs and large companies on pre-competitive, industry-driven technological research, resulting in concrete product and production innovation in the vehicle industry, the manufacturing industry, and production environments.

Goal of the internship

The detection and recognition of operator actions from a data streams is nowadays a popular challenge, with the potential to aid in operator fast training, monitoring and fault detection. In this internship the aim is to study the state of the art available techniques that address this challenge of interpreting operator actions in industrial environment.
The expected outcome is a real-time operator action detection and action recognition system.

This internship is linked to the FAMAR project, in which the overall goal is to create an economically feasible user-centred Augmented Reality application methodology for flexible assembly and inspection operations in a low volume/high mix manufacturing environment.

In this context, the goal of this internship is to perform a state of the art study of the latest research and development done in the area of operator actions recognition, oriented toward industrial applications in a controlled environment. A list of predefined actions such as: caulking, hammering and/or screwing will be selected.
Multiple vision sensors will be made available during the internship (2D and 3D) in order to validate. During this internship, after the state of art study you will have to collect and annotate data of pre-selected actions to be recognized. Then, implement, apply and benchmark the selected approaches to perform operator action recognition on the collected dataset.

Profile student

• Bachelor degree in electrical engineering, computer science, or related field;
• Knowledge of image processing, computer vision, machine learning is highly recommended;
• Good programming skills in Python or C++
• Experience in open-source deep learning frameworks such as TensorFlow or PyTorch preferred
• Passionate by research and new technologies with focus on applications that includes machine learning, deep learning and computer vision
• Result oriented, responsible and proactive;
• A good communicator, able to communicate in English;
• Eager to learn and a team player.

Only EEA or Swiss nationals can be accepted for internships due to work permit regulations.

Practical Data

This assignment is an internship but can also be executed by a thesis student from a local university.

The assignment is for min 4 month to maximum 6 months and takes place at the offices of Flanders Make offices located in Leuven, Belgium.

For internship:

All software and hardware needed for the execution of the project will be provided by Flanders Make.


  • Locatie: Gaston Geenslaan 8, 3001 Leuven


Voor meer informatie:
op het nummer: +32 16 910 614 (Ma-di-woe-do: 9u-16u)
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