Sprungmarken

Servicenavigation

Hauptnavigation


You are here:

Home Teaching Courses WS 2016/2017 Proseminar: Learning and Intelligence in Embedded Systems (Englisch)

Bereichsnavigation

Hauptinhalt

Homepage of the Proseminar "Learning and Intelligence in Embedded Systems" in WS 16/17

News and updates:

  • The grades are already submitted. Please check the BOSS system.
  • Final presentations: 15.02.2017 (please see the schedule table below).
  • Each student should select one of the topics below until the end of the next lecture on 26.11.2016. Please contact me if you need more information about the topics or the book.
  • IMPORTANT: Please refer to the introductory presentation for more information about the tasks and the regulations of the Proseminar.

Proseminar:

Learning and Intelligence in Embedded Systems

(Lernen und Intelligenz in Eingebetteten Systemen)


Description:

Embedded systems have become very widespread and used nearly everywhere. They are usually designed to perform specific predefined tasks based on a known input domain. However, many embedded systems are required to interact with new environments, that have new or unknown inputs, and provide intelligent decisions. Hence, the need arises to adopt machine learning techniques in embedded systems to be able to learn from examples and adapt to changing conditions. However, some resource-constrained embedded systems may not be able to run specific computation-intensive techniques.

In this proseminar, we will explore machine learning techniques and applications for embedded systems. Furthermore, we will discuss the techniques that are suitable for resource-constrained embedded systems.


Organization:

  • Start of course: 19.10.2016
  • Classroom sessions: Wednesdays 14:15-15:45, Seminarraum E18, OH16
  • Semester: Wintersemester 2016/17
  • Language: English
  • Lecturer: Dr. Anas Toma
  • Reference book: Intelligence for Embedded Systems - A Methodological Approach, Cesare Alippi, Springer International Publishing Switzerland 2014


Procedure:

  1. They will be an introductory presentation
  2. The students choose their topics
  3. Each student presents his topic as a rehearsal presentation for discussion, evaluation and feedback
  4. The students write a short summary report
  5. Final presentations


Schedule of the lectures and the rehearsal talks:

DateSpeakerTopic
19.10.2016 Anas Toma Introduction
26.10.2016 Anas Toma How to present
23.11.2016 Leon Schubert Emotional cognitive mechanisms
30.11.2016 Anas Toma Artificial neural networks in embedded systems 
07.12.2016 Philipp Verstege Localization and Tracking
14.12.2016 Timo Gojowczyk Energy harvesting level adaptation
21.12.2016 Hendrik Hildebrandt Passive and active learning
11.01.2017 Philipp Koppenstein Power supply voltage and processor frequency levels adaptation 
18.01.2017 Julian Hankel Adaptive sensing and its policies
25.01.2017 Mandy Nicolaus Introduction to fault diagnosis systems
01.02.2017 Anas Toma Last meeting and discussion
15.02.2017 All participants Final presentations 

Note: the presentations were scheduled randomly in the second lecture.


Presentation schedule on 15.02.2017 (Final presentations):

Time Speakers
09:30 - 11:00  Leon Schubert, Philipp Verstege and Timo Gojowczyk
11:00 - 11:10 Break
11:10 - 12:10  Hendrik Hildebrandt and Philipp Koppenstein
12:10 - 13:10 Break
13:10 - 14:10  Julian Hankel and Mandy Nicolaus