FAST -Feedback-guided Automation of Sub-tasks

Our FAST Framework helps clients with decision making tasks based on visual  information (e.g. quality inspection, medical diagnosis, …) with limited data available. Fraunhofer IKS can help to reliably automate these decisions by  identifying the samples that can be automated and delegating the remaining  samples to an expert. Unlike classical approaches we provide an easy to  deploy, early solution that improves based on the expert feedback over time.

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Challenge: Application of Machine Learning with Limited Data

The applicability of Machine Learning (ML) solutions to real world applications is often limited by  the need for large amounts of training data. Especially for small enterprises or when working with tasks that require special expertise (e.g., medical), applying ML is often impractical due to the high cost, effort and risk associated with data collection and labeling. The target group for the framework are thus users with tasks that can be automated based on visual information where an expert is available, but data is sparse.

Solution: Solving a sub-problem and Utilization of Expert Feedback

Instead of entirely solving a problem, a sub-problem is identified based on a small initial set of data. A system is deployed that is targeted to solving this sub-problem reliably (minimization of errors). Samples that do not belong to that sub-problem, and can therefore not be processed automatically, are delegated to an expert. The expert feedback can be utilized to increase the scope of the solution so that more and more samples can be automated while the system is  already in use.


  • Immediate assistance: Instead of a long data collection phase upfront a  partial solution is deployed early and already assists in the task.
  • Lower barrier & risk: Easy setup and only a small amount of initial data is  required.
  • Increase efficiency: The expert can focus on the problems that require  expertise.
  • Trust in the system: By working alongside the system, acceptance and trust  can be established

Why choose Fraunhofer IKS:

Most research focuses on “maximizing overall accuracy with few data points” while we focus on “minimizing errors on a specific subset”. This makes the system more reliable and allows for early deployment.

Our other core competencies

In addition to FAST - Feedback-guided Automation of Sub-tasks, we also focus on the following topics:

Person and Object Detection

Robust AI: Uncertainty Estimation


Industrial Sensors

The automation of production requires reliable systems for the real-time monitoring and control of processes. Visit Industrial Sensors to learn more about our focus areas and the various projects Fraunhofer IKS is working on.

​Modular Concept Learning

Standards for AI, Safety and Automation