An often used preprocessing step in text recognition systems is text line detection. The aim of this internship is to implement an existing method for text line detection. Goal Implement an existing method, which is introduced in [1]. Compare the results of your implementation with results gained in the original work. Workflow Literature review Data … Continue reading Text Line Detection
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
Supervisor: Fabian Hollaus The quality of photographs of single document pages or book pages is often limited by distortions. Dewarping techniques can be used in order to remove such distortions, i.e. rectify the document images. Goal The aim of this work is to implement a document image dewarping algorithm. The method should make use of … Continue reading Document Dewarping
Status: available Supervisors: Michael Reiter, Matthias Wödlinger Why? The target dataset is the enormous digitised collection of historical printed publications at Austrian National Library. In particular, Austrian Books Online (digitised over the last years in a large-scale cooperation with Google) and Austrian Newspapers Online from 16th to 19th century, which rank among the most important … Continue reading Document image classification of historic book pages
Problem Statement Status: vergebenSupervisor: Martin Kampel Das Theatermuseum Wien beherbergt ca. eine halbe Million Fotos. Davon wurden rund 80.000 digitalisiert und sind vor 1940 entstanden. Von vielen Dargestellten wissen wir die Namen. Aber von ebenso vielen haben wir keine Informationen. Vor allem Statist*innen, Tänzer*innen und Nebenschauspieler*innen sind heute oft schwer zu eruieren.Die Aufgabe besteht nun … Continue reading GESICHTSERKENNUNG IN DER FOTOSAMMLUNG DES THEATERMUSEUMS WIEN
Supervisors: Dominik Schörkhuber, Margrit Gelautz Distributed Deep Learning In this practicum, we aim to evaluate the feasibility of distributed deep learning for Computer Vision applications on the Vienna Scientific Cluster (VSC) (https://www.it.tuwien.ac.at/services/forschung/high-performance-computing/vsc-vienna-scientific-cluster). We are currently developing deep learning algorithms with steep requirements when it comes to computational resources for an ongoing research project in the … Continue reading Distributed Deep Learning
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. Table Structure Recognition (TSR) deals … Continue reading Table Structure Recognition
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
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