infMPInS-01a: Master project - Intelligent Systems (infMPInS-01a) (080092)- Dozentinnen/Dozenten
- Prof. Dr.-Ing. Sven Tomforde, Nils Bischoff, M.Sc.
- Angaben
- Übung, 4 SWS, ECTS-Studium, ECTS-Credits: 10
Praesenzveranstaltung, Unterrichtssprache Englisch, Kick-off meeting: 17. April 2024 um 14:15 Uhr in HRS 3, Raum 309b (Labor)
Zeit und Ort: n.V.
Vorbesprechung: 17.4.2024, 14:15 - 15:15 Uhr
- Voraussetzungen / Organisatorisches
- Abstract
An "intelligent system" is a computer system that is able to operate under difficult conditions (e.g., time-varying environments, emergent situations, or disturbances) by autonomously adapting its behavior to the changing conditions and learning on its own. We use the robot platform "TurtleBot3" as a basis for the development of intelligent systems in student projects.
Learning objectives
The participants should learn to work on a larger, coherent project from the field of intelligent systems in a limited amount of time. Emphasis is placed on independent project work and group work.
The overall goal of the course is to gain a basic understanding and experience of how intelligent systems are designed, developed and operated. In addition to the actual development of the software, the module aims to provide hands-on experience in a team of developers. Specific objectives are:
- Specification and definition of the "product" using standard software engineering tools.
- Setup of scientific experiments using standard data science libraries like NumPy, pandas, PyTorch, TensorFlow, Keras, ...
- (Self-)organization in the team, management of the process, deadline monitoring
- Entire software development process until delivery to the customer
- Documentation of the product
Your supervisors continuously monitor the process in the role of a customer, i.e. you are expected to demonstrate progress on a regular basis.
- Inhalt
- Learning content
Summer term 2024: For the visual inspection of road signs, we have several sequences of images in which a sign is recognised and identified as the same sign across the sequences. This results in a selection of images of the same object, which will now be used to assess its condition. There are several potential approaches. One possibility is to develop a solution that automatically selects the best single image. This can then be analysed for damage or other deviations from the ideal state using an anomaly detection method. Another approach would be to fuse information from different images before anomaly detection. The project group will implement and evaluate strategies for data selection or fusion as well as compare methods for visual anomaly detection. The addition of your own ideas to the suggestions described here is explicitly encouraged. The goal of the project is therefore to develop a system that can analyse road signs for visual anomalies using a selection of images.
Other requirements
No mandatory prerequisites. However, previous knowledge in the field of "Intelligent Systems" is more than helpful, ideally acquired by attending the corresponding lectures. You should have good programming skills and not be afraid of working with real hardware.
Audit performances
Presentations, report, scientific paper and the realized software system (including documentation).
Contact
Interested students may contact the group (Nils Bischoff) for more details. You can also do this to "book a place" in the project already during the preceeeding term.
- Zusätzliche Informationen
- Erwartete Teilnehmerzahl: 6
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