About

Education

What I learned.
The Path I Choose: A Journey Through Learning
  1. Doctoral Degree Engineering ongoing

    @ Technical University of Munich, Germany
  2. M. Sc. Electrical Engineering and Information Technology 2017

    @ Technical University of Munich, Germany
  3. Research Internship 2016

    @ The University Centre in Svalbard, Norway
  4. Study Abroad 2015

    @ Norwegian University of Science and Technology, Trondheim, Norway
  5. B. Sc. Electrical Engineering and Information Technology 2014

    @ Technical University of Munich, Germany

Publications

What I published.
Words That Inform - Ideas That Transform
  1. Tackling Face Verification Edge Cases: In-Depth Analysis and Human-Machine Fusion Approach 2023@MVA

    GitHub Repo
  2. Explainable Model-Agnostic Similarity and Confidence in Face Verification 2023@WACV-W

    GitHub Repo Website
  3. Octuplet-Loss: Make Face Recognition Robust to Image Resolution 2023@FG

    GitHub Repo
  4. Susceptibility to Image Resolution in Face Recognition and Training Strategies to Enhance Robustness 2022@LITES-Journal

    GitHub Repo
  5. Face Morphing: Fooling a Face Recognition System Is Simple! 2022

  6. Cross-Quality LFW: A Database for Analyzing Cross-Resolution Image Face Recognition in Unconstrained Environments 2021@FG

    GitHub Repo Website
  7. Facial Landmark Detection 2017@GCPR

    GitHub Repo
  8. Face Aggregation Network For Video Face Recognition 2021@ICIP

  9. A multi-task comparator framework for kinship verification 2020@FG

  10. Outlier-Robust Neural Aggregation Network for Video Face Identification 2019@ICIP

  11. Attention-based partial face recognition 2021@ICIP

    GitHub Repo
  12. Attention fusion for audio-visual person verification using multi-scale features 2020@FG

  13. A Coarse-to-Fine Dual Attention Network for Blind Face Completion 2021@FG

    GitHub Repo
  14. A system for automated vision-based sea-ice concentration detection and floe-size distribution indication from an icebreaker 2017@OMAE

    GitHub Repo

Projects

What I did.
Turning Ideas Into Reality: Projects That Matter

Principles

What I believe in.

Values That Guide - Actions That Speak
Ethical AI Development

Ethics shouldn't be an afterthought in machine learning. I prioritize transparent and unbiased algorithms to ensure fairness and accountability.

Continuous Learning

The field of machine learning is ever-evolving. I am committed to continuous learning to stay ahead of new techniques and technologies.

Open Communication

A free flow of information is essential for project success. I emphasize transparent and open dialogues to solve problems efficiently and creatively.

Handcrafted with by Martin Knoche © twentytwentythree