Quaternionic networks have emerged as a lightweight alternative to standard neural
networks. We propose using a Quaternionic conditional Generalized Adversarial Network …

Document image enhancement and binarization methods are often used to improve the
accuracy and efficiency of document image analysis tasks such as text recognition …

Binarization is often the first step in many document analysis tasks and plays a key role in
the subsequent steps. In this paper, we formulate binarization as an image-to-image …

Document image enhancement and binarization methods are often used to improve the
accuracy and efficiency of document image analysis tasks such as text recognition …

For document image analysis, image binarization is an important preprocessing step. Also,
binarization can help in improving the readability of old and historical manuscripts. Such …

Deep neural networks are widely used in various AI systems. Many such systems rely on the
edge computing concept and try to perform computations on end devices while still being …

U-Net similar architectures are widely used in the task of document image binarization.
However, despite the good quality of binarization, they also have high computational …

Document binarization is a key step in most document analysis tasks. However, historical-
document images usually suffer from various degradations, making this a very challenging …

Degraded document image binarization is one of the most challenging tasks in the domain
of document image analysis. In this paper, we present a novel approach towards document …

Color image binarization plays a pivotal role in image preprocessing work and significantly
impacts subsequent tasks, particularly for text recognition. This paper concentrates on …