A persistent challenge in the cognitive development of autonomous robotics is the
unsupervised and unstructured nature of skill transfer learning where the Self Organizing …

Few-shot classification is a challenge in machine learning where the goal is to train a
classifier using a very limited number of labeled examples. This scenario is likely to occur …

With the widespread use of social media, companies now have access to a wealth of
customer feedback data which has valuable applications to Customer Relationship …

The self-organizing map (SOM) model is an effective technique applicable in a wide range
of areas, such as pattern recognition and image processing. In the SOM model, the most …

High-dimensional data is pervasive in many fields such as engineering, geospatial, and
medical. It is a constant challenge to build tools that help people in these fields understand …

Modelling three-dimensional virtual objects in the context of architectural, product and game
design requires elaborate skill in handling the respective CAD software and is often tedious …

Depuis son introduction en 1982, la carte auto-organisatrice de Kohonen (Self-Organizing
Map: SOM) a prouvé ses capacités de classification et visualisation des données …

The capability for understanding data passes through the ability of producing an effective
and fast classification of the information in a time frame that allows to keep and preserve the …

The brain's cortical plasticity is one of the main features that enable our capability to learn
and adapt in our environment. Indeed, the cerebral cortex has the ability to self-organize …

Abstract Machine learning techniques applied to data-mining face the challenge of time and
memory requirements, and for this purpose should make full profit of the increase in power …