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

Removing degradation from document images not only improves their visual quality and
readability, but also enhances the performance of numerous automated document analysis …

Degraded document binarization has received keen attention due to its vital influence on
subsequent document analysis tasks. In this study, we propose a novel Degraded Document …

Unpaired image super-resolution (SR) has recently attracted considerable attention in the
unsupervised SR community. In contrast to supervised SR, existing unpaired SR methods …

Driving can understand the importance of tire tread depth and air pressure, but most people
are unaware of the safety risks of tire oxidation. Drivers must maintain vehicle tire quality to …

Palm leaf manuscripts offer a rich source of data critical for document analysis tasks,
including character, word, and text analysis. However, their cleaning and denoising present …

Document binarization is a crucial pre-processing step for various document analysis tasks.
However, existing methods fail to accurately capture stroke edges, primarily due to the …

Ballistic impacts are a primary risk in both civil and military defence applications, where
successfully predicting the dynamic response of a material or structure to impact crucial to …

The efficient segmentation of foreground text information from the background in degraded
color document images is a critical challenge in the preservation of ancient manuscripts. The …

The large amount of sensitive personal information used in deep learning models has
attracted considerable attention for privacy security. Sensitive data may be memorialized or …