Teaching

Text Recognition in Graffiti Images

Status: taken Supervisor: Sebastian Zambanini Problem Statement The INDIGO project aims to document and analyze the graffiti along Vienna’s Donaukanal. However, indexing graffiti images by written text is a time-consuming task. Hence, a system which provides automatic guesses for written text would be highly beneficial. Goal The goal of this work is to explore and … Continue reading Text Recognition in Graffiti Images

Change Detection in Graffiti Images

Status: taken Supervisor: Sebastian Zambanini Problem Statement The INDIGO project aims to document and analyze the graffiti along Vienna’s Donaukanal. One of the main problems faced is monitoring new graffiti. Instead of solely relying on Instagram and human memory, an automatic change detection between images from different time stamps can support the monitoring process. Goal … Continue reading Change Detection in Graffiti Images

Diploma Thesis – Assisted/Automated Driving

The Computer Vision Lab  at TU Wien announces a research position for a Diploma/Master Student   to work on the “SyntheticCabin” project starting in October 2022 (or later). We are looking for a highly motivated diploma/master student of Informatics (or related studies) with a background in computer vision and machine learning and a strong interest … Continue reading Diploma Thesis – Assisted/Automated Driving

Automated Analysis of NHM Herbarium Collection

Supervisor: Michael Reiter, Florian Kleber Start: as soon as possible Problem Statement A herbarium is a collection of preserved plant specimens with information from the collector and additional data. The Herbarium of the Natural History Museum in Vienna (W) was established in 1807 and is now ranked amongst the top five botanical collections in the … Continue reading Automated Analysis of NHM Herbarium Collection

Evaluating Augmented Reality Frameworks for Real-time On-device Product Recognition

Status: open Supervisor: Martin Kampel, Julian Strohmayer Problem Statement: The ever growing product assortments of supermarkets present consumers with interesting challenges. For example, it is often difficult for health- or environmentally-conscious consumers to filter out products that are in line with their personal values from the overabundance of products. To support these consumers, mobile applications … Continue reading Evaluating Augmented Reality Frameworks for Real-time On-device Product Recognition

Selected Topics in Active Assisted Living in collaboration with a company

The following topics are part of our collaboration with Cogvis Gmbh, For processing deep learning networks, Cogvis as well as CVL have powerful hardware available which can be used. All Master students get an internal company supervisor who is responsible for the topic and the guidance of the students. A renumeration and/working place is possible. … Continue reading Selected Topics in Active Assisted Living in collaboration with a company

Vehicle Detection in a Sequence of SAT Images

Problem Statement Object detection is a very important and still unsolved problem in object recognition. For example, the problem becomes challenging in aerial imaging and remote sensing as the scenes and the data differ significantly from the case usually considered in computer vision. The aim of this thesis is to study vehicle detection for a … Continue reading Vehicle Detection in a Sequence of SAT Images

Evaluating different transformer architectures for cell classification in Flow Cytometry Data 

Supervisor: Michael Reiter  Background  Flow Cytometry is a laser-based technique to measure antigen expression levels of blood cells. It is used in research as well as in daily clinical routines for immunophenotyping and for monitoring residual numbers of cancer cells during chemotherapy. One patient’s sample contains approximately 50-300k cells (also called events) with up to … Continue reading Evaluating different transformer architectures for cell classification in Flow Cytometry Data 

Designing efficient Data Augmentation Strategies for Flow Cytometry Data 

Supervisor: Michael Reiter  Background  Flow Cytometry is a laser-based technique to measure antigen expression levels of blood cells. It is used in research as well as in daily clinical routines for immunophenotyping and for monitoring residual numbers of cancer cells during chemotherapy. One patient’s sample contains approximately 50-300k cells (also called events) with up to … Continue reading Designing efficient Data Augmentation Strategies for Flow Cytometry Data 

Multi-step classification of flow cytometry cell data with set transformers 

Supervisors: Michael Reiter, Matthias Wödlinger, Florian Kowarsch Background  Flow Cytometry is a laser-based technique to measure antigen expression levels of blood cells. It is used in research as well as in daily clinical routines for immunophenotyping and for monitoring residual numbers of cancer cells during chemotherapy. One patient’s sample contains approximately 50-300k cells (also called … Continue reading Multi-step classification of flow cytometry cell data with set transformers