Martin Mayr

Martin Mayr, M. Sc.

Researcher

Department of Computer Science
Chair of Computer Science 5 (Pattern Recognition)

Room: Room 04.159
Martensstr. 3
91058 Erlangen

  • Since 08/2019:
    Ph.D. Student at the Pattern Recognition Lab
  • 10/2016 – 07/2019:
    M.Sc. in Computer Science:
    Friedrich-Alexander University Erlangen-Nürnberg
  • 03/2012 – 07/2016:
    B.Sc. in Business Information Technology:
    Regensburg University of Applied Sciences

  • Kommunikation und Sprache im Reich. Die Nürnberger Briefbücher im 15. Jahrhundert: Automatische Handschriftenerkennung - historische und sprachwissenschaftliche Analyse.

    (Third Party Funds Single)

    Term: October 1, 2019 - September 30, 2022
    Funding source: DFG-Einzelförderung / Sachbeihilfe (EIN-SBH)

No projects found.

2022

Conference Contributions

2021

Conference Contributions

2020

Conference Contributions

2019

Conference Contributions

Praktikum (PR)

  • Projekt Computer Vision

    This course will be held online until the coronavirus pandemic is contained to such an extent that the Bavarian state government can allow face-to-face teaching again

    Basic knowledge of image processing is desirable. In the first session there will be a short recap on image representation and basic image filtering techniques. However, having visited lectures such as Introduction to Pattern Recognition (IntroPR) or Diagnostic Medical Image Processing (DMIP) might prove beneficial.

    Please contact us if you have any questions. You can register via Studon (https://www.studon.fau.de/crs4397541.html) for the Computer Vision Project. During the semester lecture and exercise alternate on a weekly basis. Exercises are supervised and take place in one of the CIP pools. All exercises must be completed.

    You can get either 5 or 10 ECTS credits for this project. The following options are available:

    5 ECTS (counts as: Hochschulpraktikum)

    This option requires:

    • lectures (strongly recommended as they introduce the background required for the exercises)
    • exercises (in groups of 2 people) need to be finished on time
    • individual presentation about a state-of-the-art research paper at the end of the semester (graded if needed)

    10 ECTS (counts as Hochschulpraktikum (5 ECTS) + Forschungspraktikum (5 ECTS), or Master Project Computer Science (10 ECTS))

    • lectures (strongly recommended as they introduce the background required for the exercises)
    • exercises (in groups of 2 people) need to be finished on time
    • individual coding/research project under supervision of a LME PhD student at the end of regular schedule (graded if needed)

    Important: You cannot use the lecture/exercise part as a 5 ECTS research project (Forschungspraktikum). Please contact one of the PhD students at the lab if you need a research project.

    • Expected participants: 14; ECTS-Studium (ECTS-Credits: 10)
    • Termin:
      • Mo 12:00-14:00, Room Übung 3 / 01.252-128 (exclude vac) ICS
      • Mo 12:00-14:00, Room 00.156-113 CIP (exclude vac) ICS

Praktikum (PR)

  • Projekt Computer Vision

    This course will be held online until the coronavirus pandemic is contained to such an extent that the Bavarian state government can allow face-to-face teaching again

    Basic knowledge of image processing is desirable. In the first session there will be a short recap on image representation and basic image filtering techniques. However, having visited lectures such as Introduction to Pattern Recognition (IntroPR) or Diagnostic Medical Image Processing (DMIP) might prove beneficial.

    Please contact us if you have any questions. You can register via Studon (https://www.studon.fau.de/crs4397541.html) for the Computer Vision Project. During the semester lecture and exercise alternate on a weekly basis. Exercises are supervised and take place in one of the CIP pools. All exercises must be completed.

    You can get either 5 or 10 ECTS credits for this project. The following options are available:

    5 ECTS (counts as: Hochschulpraktikum)

    This option requires:

    • lectures (strongly recommended as they introduce the background required for the exercises)
    • exercises (in groups of 2 people) need to be finished on time
    • individual presentation about a state-of-the-art research paper at the end of the semester (graded if needed)

    10 ECTS (counts as Hochschulpraktikum (5 ECTS) + Forschungspraktikum (5 ECTS), or Master Project Computer Science (10 ECTS))

    • lectures (strongly recommended as they introduce the background required for the exercises)
    • exercises (in groups of 2 people) need to be finished on time
    • individual coding/research project under supervision of a LME PhD student at the end of regular schedule (graded if needed)

    Important: You cannot use the lecture/exercise part as a 5 ECTS research project (Forschungspraktikum). Please contact one of the PhD students at the lab if you need a research project.

    • Expected participants: 14; ECTS-Studium (ECTS-Credits: 10)
    • Termin:
      • Mo 12:00-14:00, Room Übung 3 / 01.252-128 (exclude vac) ICS
      • Mo 12:00-14:00, Room 00.156-113 CIP (exclude vac) ICS
Friedrich-Alexander-Universität Erlangen-Nürnberg