700.398 (24S) Research Seminar on "Neurocomputing and Machine Learning in Intelligent Transportation"

Sommersemester 2024

Anmeldefrist abgelaufen.

Erster Termin der LV
22.03.2024 11:45 - 13:15 B04.2.110 On Campus
Nächster Termin:
03.05.2024 11:45 - 13:15 B04.2.110 On Campus

Überblick

Lehrende/r
LV-Titel englisch Research Seminar on "Neurocomputing and Machine Learning in Intelligent Transportation"
LV-Art Seminar (prüfungsimmanente LV )
LV-Modell Präsenzlehrveranstaltung
Semesterstunde/n 2.0
ECTS-Anrechnungspunkte 4.0
Anmeldungen 7 (20 max.)
Organisationseinheit
Unterrichtssprache Englisch
mögliche Sprache/n der Leistungserbringung Deutsch
LV-Beginn 22.03.2024
eLearning zum Moodle-Kurs
Anmerkungen

      

Zeit und Ort

Liste der Termine wird geladen...

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

GLOBAL PLAN:
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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 in 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?)

Erwartete Vorkenntnisse

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Curriculare Anmeldevoraussetzungen

                

Literatur

            

               

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Link auf weitere Informationen

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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.

Prüfungsmethode/n

The grading will be based on the project results,  presentations and an exposé at the end of the course.

Prüfungsinhalt/e

topics are related to the project

Beurteilungskriterien/-maßstäbe

the standards of assessment for examinations are given by fulfilling requirements of the written exam

Beurteilungsschema

Note Benotungsschema

Position im Curriculum

  • Masterstudium Artificial Intelligence and Cybersecurity (SKZ: 993, Version: 20W.1)
    • Fach: Specialisation in Artificial Intelligence and Cybersecurity (Wahlfach)
      • Fachlich relevante Lehrveranstaltungen ( 0.0h XX / 34.0 ECTS)
        • 700.398 Research Seminar on "Neurocomputing and Machine Learning in Intelligent Transportation" (2.0h SE / 4.0 ECTS)
          Absolvierung im 2., 3. Semester empfohlen
  • 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)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 22W.1)
    • Fach: Information and Communicatons Enginnering: Supplements (Wahlfach)
      • 1.3a 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: 22W.1)
    • Fach: ICE- Supplements (Wahlfach)
      • 2.3a 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 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 2021
  • 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)