Nowadays, deep learning methods are employed in a broad range of research fields. The
analysis and recognition of historical documents, as we survey in this work, is not an …

Constructing high-quality character image datasets is challenging because real-world
images are often affected by image degradation. There are limitations when applying current …

Quantum neural networks are emerging as poten-tial candidates to leverage noisy quantum
processing units for applications. Here we introduce hybrid quantum-classical au-to …

This article develops theoretical, algorithmic, perceptual, and interaction aspects of script
legibility enhancement in the visible light spectrum for the purpose of scholarly editing of …

Transcribing struck-through, handwritten words, for example for the purpose of genetic
criticism, can pose a challenge to both humans and machines, due to the obstructive …

The identification and restoration of ancient watermarks have long been a major topic in
codicology and history. Classifying historical documents based on watermarks can be …

The article presents a textual Big Data analytics solution developed in a real setting as a part
of a high-capacity document digitization and storage system. A software based on machine …

This paper presents a comprehensive study on the possible hybrid quantum-classical
autoencoder architectures for end-to-end radio communication against noisy channel …

Physical damages (such as torn-offs and scratches) are commonly seen in historical
documents. Recognition of such damages is currently absent in digitization-and-information …

The environmental noises caused by the bad weather and some obstacles are the main
problem for computers to identify whether the mango leaves are diseased or not, which …