51 citations · 203 across the 18 of their papers we have counts for
15 papers · 1 filter
Weakly Supervised Scene Text Detection using Deep Reinforcement Learning
Emanuel Metzenthin, Christian Bartz, Christoph Meinel
The challenging field of scene text detection requires complex data annotation, which is time-consuming and expensive. Techniques, such as weak supervision, can reduce the amount o…
Handwriting Classification for the Analysis of Art-Historical Documents
Christian Bartz, Hendrik Rätz, Christoph Meinel
Digitized archives contain and preserve the knowledge of generations of scholars in millions of documents. The size of these archives calls for automatic analysis since a manual an…
One Model to Reconstruct Them All: A Novel Way to Use the Stochastic Noise in StyleGAN
Christian Bartz, Joseph Bethge, Haojin Yang +1
Generative Adversarial Networks (GANs) have achieved state-of-the-art performance for several image generation and manipulation tasks. Different works have improved the limited und…
Improving the Evaluation of Generative Models with Fuzzy Logic
Julian Niedermeier, Gonçalo Mordido, Christoph Meinel
Objective and interpretable metrics to evaluate current artificial intelligent systems are of great importance, not only to analyze the current state of such systems but also to ob…
KISS: Keeping It Simple for Scene Text Recognition
Christian Bartz, Joseph Bethge, Haojin Yang +1
Over the past few years, several new methods for scene text recognition have been proposed. Most of these methods propose novel building blocks for neural networks. These novel bui…
Multi-Task Generative Adversarial Network for Handling Imbalanced Clinical Data
Mina Rezaei, Haojin Yang, Christoph Meinel
We propose a new generative adversarial architecture to mitigate imbalance data problem for the task of medical image semantic segmentation where the majority of pixels belong to a…