Informatik Praktika

Informatik Praktika

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 →

Diplomarbeiten, Informatik Praktika

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 →

Diplomarbeiten, Informatik Praktika

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 →

Diplomarbeiten, Informatik Praktika

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  →

Informatik Praktika

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  →

Diplomarbeiten, Informatik Praktika

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  →

Diplomarbeiten, Informatik Praktika

CNN based classification of Flow Cytometry Data

Supervisor: Michael Reiter, 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 events) with … Continue reading CNN based classification of Flow Cytometry Data →

Informatik Praktika

Handwritten Text Recognition

Offline Handwritten Text Recognition (HTR) describes the task of transcribing handwritten text into digital texts. Compared to Optical Character Recognition (OCR), HTR is much more challenging and still an open problem.Recently, a transformer based framework named TrOCR was suggested in [1]. Goal The aim of this internship is to fine-tune existing HTR models in [1] … Continue reading Handwritten Text Recognition →