This paper presents a comprehensive survey of research works on the topic of form
understanding in the context of scanned documents. We delve into recent advancements …

For efficient disaster management, it is essential to identify and categorize natural disasters.
The classical approaches and current technological advancements for identifying …

Text classification is a central task in Natural Language Processing (NLP) that aims at
categorizing text documents into predefined classes or categories. It requires appropriate …

To reliably and accurately classify complicated" big" datasets, machine learning models
must be continually improved. This research proposes straightforward yet competitive neural …

With the rapid advancement of the internet, there has been a dramatic increase in short-text
data. Due to the brevity of short texts, sparse features, and limited contextual information …

Extracting valuable insights from vast amounts of unstructured digital text presents
significant challenges across diverse domains. This research addresses this challenge by …

In this paper, we present a software tool called PocketFinderGNN for the recognition of a
critical manufacturing feature named close pocket in 3D models. The close pocket is a …

The widespread availability of digitized fine art collections in museums and galleries has
generated a demand for efficient software tools. These tools enable rapid retrieval and …

Discourse parsing in multi-party dialogue aims to extract the relationships between
elementary discourse units (EDUs) such as arguments and utterances, and has numerous …

Exploiting heterogeneous information in attributed networks to improve the performance of
community detection has attracted considerable research attention. Although variational …