Supervisor: Florian Kleber Start: as soon as possible Problem Statement Document Image Analysis (DIA) deals with the analysis and recognition of document images. Tasks range from skew estimation, layout analysis to Handwritten Text Recognition (HTR). Tables in documents contain structured information which can allow a deeper insight into specific data. During layout analysis, one task … Continue reading Table Detection
The seminar provides a forum for discussion of master students’ work and an opportunity for students to share ideas and news. Procedure: The following deliverables are part of the evaluation of this seminar: MTS (Master Thesis Specification) presentation: After the formal application for the master thesis at the study deans in TISS (see the faculty … Continue reading Seminar für Diplomand_innen für Visual Computing
Supervisor: Michael Reiter (CVL), Manfred Lehner (CCRI) Praktikum/Bachelorarbeit mit Möglichkeit zur Fortführung im Rahmen einer Diplomarbeit in Zusammenarbeit mit dem Christian Doppler Laborator für CAR-T-Zellen der nächsten Generation Dieses CD Labor an der St. Anna Kinderkrebsforschung arbeitet an molekularen Werkzeugen zur Verbesserung der sogenannten CAR-T-Zell-Therapie, einer Krebstherapie, welche auf der Verabreichung von genetisch veränderten Immunzellen beruht. … Continue reading Verbesserung der CAR-T-Zellen Therapie durch Datenanalyse
Status: available Supervisor: Manuel Keglevic Why? Law enforcement agencies possess an extensive collection of handwritten documents. This includes for example documents belonging to open cases, for example death threats, and reference samples from suspects and prisoners. Yet, these collections of documents can only be utilized to a limited extend, since for an identification of an … Continue reading Deep Learning-based Forensic Writer Retrieval/Document Segmentation
Supervisor: Florian Kleber, Simon Brenner Start: as soon as possible Problem Statement Historical maps contain a lot of information like land boundarys or outlines of buildings. To show the development of citys and different regions it is necessary to extract this information from historical maps. Within this work the main goal will be detect the … Continue reading Segmentation of houses in historical Maps
Status: available Supervisor: Daniel Helm, Martin Kampel Start: as soon as possible Problem Statement Automatic scene analysis is a crucial task for historians or film archivists in order to preserve and interpret the memories of human cultural history. Film archives include thousands of hours of digitized analog footage from the last 100 years up to … Continue reading Relation Detection: Image Similarity Measurement in Large Historical Archives
Status: available Supervisor: Daniel Helm, Martin Kampel Start: as soon as possible Problem Statement Automatic video analysis in large historical film collections is a challenging task due to different aspects. One major challenge is related to the quality of historical films, e.g. over-, underexposures and blur. Furthermore, they include scratches, cracks or press cuts and … Continue reading Historical Image Restoration: Deep learning-based versus traditional-based deformation strategies
Status: available Supervisor: Daniel Helm, Martin Kampel Start: as soon as possible Problem Statement Automatic video content analysis is needed in many different domains such as historical film preservation or film archiving. Due to the enormous quantity of available visual media data, automatic approaches shall be used in order to find specific content in videos … Continue reading Camera Pose Estimation for Video Shot Analysis
Status: open Supervisor: Robert Sablatnig Problem Statement Detecting and tracking moving objects is a challenging task, since the objects’ optical signature is less discriminative due to occurring motion artifacts, occlusions in the wild and dynamic backgrounds. Goal The goal of this practical training project is to explore and examine methods that can be used to … Continue reading Automatic Ball Detection in Soccer, Golf and Tennis Games
Status: open Supervisor: Sebastian Zambanini Problem Statement Detecting and classifying objects in remote sensing images is a challenging task, since the objects’ optical signature is less discriminative due to the small resolution. Common object detection methods in this area aim to find object locations by classifying local structures, while neglecting the larger surroundings of the … Continue reading Exploiting Context in Remote Sensing Object Detection