Purpose By mapping-out the capabilities, challenges and limitations of named-entity
recognition (NER), this article aims to synthesise the state of the art of NER in the context of …

The extraction of relevant information carried out by named entities in handwriting
documents is still a challenging task. Unlike traditional information extraction approaches …

Deep learning methods have been introduced for fault diagnosis of rotating machinery. Most
methods have good performance when processing bearing data at a certain rotating speed …

In the last years, the consolidation of deep neural network architectures for information
extraction in document images has brought big improvements in the performance of each of …

Many historical manuscripts that hold trustworthy memories of the past societies contain
information organized in a structured layout (eg census, birth or marriage records). The …

The extraction of relevant information from historical handwritten document collections is
one of the key steps in order to make these manuscripts available for access and searches …

When extracting information from handwritten documents, text transcription and named
entity recognition are usually faced as separate subsequent tasks. This has the …

Detecting the correct orientation of an image is an important part of computer vision and the
image processing pipeline. To determine the orientation of abstract paintings, as a special …

Several approaches to shadow removal in color images have been introduced in recent
years. Yet these methods fail in removing shadows that are cast on curved surfaces, as well …

The shift from one-hot to distributed representation, popularly referred to as word embedding
has changed the landscape of natural language processing (nlp) and information retrieval …