10 citations · 17 across the 6 of their papers we have counts for
7 papers
BullingerDB: A Dataset for Handwritten Text Recognition and Writer Retrieval
Marco Peer, Anna-Scius Bertrand, Patricia Scheurer +1
We present BullingerDB, a large-scale benchmark dataset for historical document analysis based on the correspondence of Heinrich Bullinger (1504-1575). The corpus comprises 20,898…
Prediction of Grade, Gender, and Academic Performance of Children and Teenagers from Handwriting Using the Sigma-Lognormal Model
Adrian Iste, Kazuki Nishizawa, Chisa Tanaka +4
Digital handwriting acquisition enables the capture of detailed temporal and kinematic signals reflecting the motor processes underlying writing behavior. While handwriting analysi…
From Pen Strokes to Sleep States: Detecting Low-Recovery Days Using Sigma-Lognormal Handwriting Features
Chisa Tanaka, Andrew Vargo, Anna Scius-Bertrand +2
While handwriting has traditionally been studied for character recognition and disease classification, its potential to reflect day-to-day physiological fluctuations in healthy ind…
Zero-Shot Prompting and Few-Shot Fine-Tuning: Revisiting Document Image Classification Using Large Language Models
Anna Scius-Bertrand, Michael Jungo, Lars Vögtlin +2
Classifying scanned documents is a challenging problem that involves image, layout, and text analysis for document understanding. Nevertheless, for certain benchmark datasets, nota…
Impact of Ground Truth Quality on Handwriting Recognition
Michael Jungo, Lars Vögtlin, Atefeh Fakhari +4
Handwriting recognition is a key technology for accessing the content of old manuscripts, helping to preserve cultural heritage. Deep learning shows an impressive performance in so…
The RPM3D project: 3D Kinematics for Remote Patient Monitoring
Alicia Fornés, Asma Bensalah, Cristina Carmona-Duarte +9
This project explores the feasibility of remote patient monitoring based on the analysis of 3D movements captured with smartwatches. We base our analysis on the Kinematic Theory of…
DIVA-DAF: A Deep Learning Framework for Historical Document Image Analysis
Lars Vögtlin, Anna Scius-Bertrand, Paul Maergner +2
Deep learning methods have shown strong performance in solving tasks for historical document image analysis. However, despite current libraries and frameworks, programming an exper…