700.398 (21S) Research Seminar on "Neurocomputing and Machine Learning in Intelligent Transportation"

Sommersemester 2021

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Erster Termin der LV
12.03.2021 12:00 - 14:00 Online Off Campus
... keine weiteren Termine bekannt

Überblick

Bedingt durch die COVID-19-Pandemie können kurzfristige Änderungen bei Lehrveranstaltungen und Prüfungen (z.B. Absage von Präsenz-Lehreveranstaltungen und Umstellung auf Online-Prüfungen) erforderlich sein.

Weitere Informationen zum Lehrbetrieb vor Ort finden Sie unter: https://www.aau.at/corona.
Lehrende/r
LV-Titel englisch Research Seminar on "Neurocomputing and Machine Learning in Intelligent Transportation"
LV-Art Seminar (prüfungsimmanente LV )
LV-Modell Onlinelehrveranstaltung
Semesterstunde/n 2.0
ECTS-Anrechnungspunkte 4.0
Anmeldungen 11 (20 max.)
Organisationseinheit
Unterrichtssprache Englisch
LV-Beginn 12.03.2021
eLearning zum Moodle-Kurs

Zeit und Ort

Beachten Sie bitte, dass sich aufgrund von COVID-19-Maßnahmen die derzeit angezeigten Termine noch ändern können.
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LV-Beschreibung

Intendierte Lernergebnisse

In this Seminar,  the student obtains a basic and broad overview of Machine Learning tools/methods, which are crucially used in several interesting use-cases in the frame  of Intelligent Transportation Systems. Furthers, he shall conduct a comprehensive literature review w.r.t. to selected topics or use-cases in the described context.


Selected applications fields  of ITS in which Machine Learning (AI / Deep Learning) does play a very crucial role are:

# Autonomous driving cars
# Driver Monitoring Systems
# Industry 4.0 in Transportation and Logistics
# Cooperative intelligent transportation systems
# Social networks impact in/for intelligent mobility systems
# Traffic Lights  Assistance systems
# Analysis of the potential synergy between Electric Vehicles and Smart Electric Grids


Lehrmethodik inkl. Einsatz von eLearning-Tools

GLOBAL PLAN:
###########
1) Kick-Off Meeting (at Semester begin): introductory presentation,  topics selection by the student, brief overview of related papers and documents.

2) Intermediate Presentations (weekly): here, students present their mini-seminars outcomes. A related feedback is provided.

3) Final presentations: second or last week  June. 


Inhalt/e

(1) Automated Machine Learning (what it is? + 1 potential application example in ITS?)
(2) Deep Autoencoder (what it is? + 1 potential application example in ITS?)
(3) Denoising Autoencoder (what it is? + 1 potential application example in ITS?)
(4) LSTM (what it is? + 1 potential application example in ITS?)
(5) Generative Adversarial Networks (what it is? + 1 potential application example in ITS?)(6) Spiking Neural Networks (what it is? + 1 potential application example in ITS?)
(7) Restricted Bolzmann Machines (what it is? + 1 potential application example in ITS?)
(8) Deep-Belief Neural Networks (what it is? + 1 potential application example in ITS?)
(9) Reinforcement Learning (what it is? + 1 potential application example in ITS?)
(10) Graph Analytics and Deep Learning (what it is? + 1 potential application example in ITS?)(11) Convolution Neural Networks (what it is? + 1 potential application example in ITS?)

Prüfungsinformationen

Im Fall von online durchgeführten Prüfungen sind die Standards zu beachten, die die technischen Geräte der Studierenden erfüllen müssen, um an diesen Prüfungen teilnehmen zu können.

Beurteilungsschema

Note Benotungsschema

Position im Curriculum

  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Information and Communications Engineering: Supplements (NC, ASR) (Wahlfach)
      • Research Seminar aus einem Bereich der Informationstechnik ( 0.0h SE / 4.0 ECTS)
        • 700.398 Research Seminar on "Neurocomputing and Machine Learning in Intelligent Transportation" (2.0h SE / 4.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Information and Communications Engineering: Supplements (NC, ASR) (Wahlfach)
      • Research Seminar aus einem Bereich der Informationstechnik ( 0.0h SE / 4.0 ECTS)
        • 700.398 Research Seminar on "Neurocomputing and Machine Learning in Intelligent Transportation" (2.0h SE / 4.0 ECTS)

Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung

Sommersemester 2024
  • 700.398 SE Research Seminar on "Neurocomputing and Machine Learning in Intelligent Transportation" (2.0h / 4.0ECTS)
Sommersemester 2023
  • 700.398 SE Research Seminar on "Neurocomputing and Machine Learning in Intelligent Transportation" (2.0h / 4.0ECTS)
Sommersemester 2022
  • 700.398 SE Research Seminar on "Neurocomputing and Machine Learning in Intelligent Transportation" (2.0h / 4.0ECTS)
Sommersemester 2020
  • 700.398 SE Research Seminar on "Neurocomputing and Machine Learning in Intelligent Transportation" (2.0h / 4.0ECTS)
Sommersemester 2019
  • 700.398 SE Research Seminar in Intelligent Transportation Systems (2.0h / 4.0ECTS)
Sommersemester 2017
  • 700.398 SE Research Seminar in Transportation Informatics (2.0h / 4.0ECTS)
Sommersemester 2016
  • 700.398 SE Research Seminar in Transportation Informatics (2.0h / 4.0ECTS)
Sommersemester 2015
  • 700.398 SE Research Seminar in Transportation Informatics (2.0h / 6.0ECTS)
Sommersemester 2014
  • 700.398 SE Research Seminar in Transportation Informatics (2.0h / 6.0ECTS)
Sommersemester 2013
  • 700.398 SE Research Seminar in Transportation Informatics (2.0h / 6.0ECTS)