Qualitative Spatial and Temporal Reasoning, or QSTR for short, is a major research area in AI that deals with the fundamental cognitive concepts of space and time in an abstract, human-like manner. For instance, in natural language one uses expressions ...

Apparel product development is an iterative problem-solving process that is heuristic in nature and involves turning 2D flat patterns into a 3D garment that would fit human anatomy. The digital transformation trend in the apparel industry will ...

In this work we present an approach for human activity recognition which is based on skeletal motion, i.e., the motion of skeletal joints in the 3D space. More specifically, we propose the use of 4 well-known image transformations (i.e., DFT, FFT, DCT, ...

In recent years, considerable advancements have been made in the area of Generative Adversarial Networks (GANs), particularly with the advent of style-based architectures that address many key shortcomings - both in terms of modeling capabilities and ...

Factorizing a multiagent system refers to partitioning the state-action space to individual agents and defining the interactions between those agents. This so-called agent factorization is of much importance in real-world industrial settings, and is a ...

Entity Linking (EL) aligns entity mentions in text to entries in a knowledge base. It usually comprises of two phases: candidate generation and candidate ranking. While most methods focus on the latter phase, it is candidate generation that sets the ...

In human resource management of large organisations, finding the best candidate for a job description requires an extensive examination of a large number of resume profiles. Even with the advent of Deep Information Retrieval and the supported semantic ...

The marine environment is a place for the production of a variety of goods in various fields of global economy. In addition, through the study of seabed geomorphological features it is possible to draw conclusions about the tectonic mechanisms of the ...

Drones and Electric Vehicles (EVs) are two technologies that are growing fast and have the potential to revolutionize the transportation sector. In this paper, we take inspiration from a recent patent submitted by Amazon, and we study the problem of ...

Explainable AI is an emerging field providing solutions for acquiring insights into automated systems’ rationale. It has been put on the AI map by suggesting ways to tackle key ethical and societal issues. Existing explanation techniques are often not ...

The existence of pre-trained deep learning models for image classification, such as those trained on the well-known Resnet-50 architecture, allows for easy application of transfer learning to several domains including image retrieval. Recently, we ...

The use of Electric Vehicles (EVs) is a main pathway to decrease CO2 emissions. Apart from mobility services, EVs can also utilize their batteries when they are not en route to increase the storage capacity of the electricity network. This in turn can ...

The evolution of natural language processing (NLP) has drastically improved numerous applications in terms of quality of results and speed, like the use of semantic search in modern search engines. NLP has highly benefited from the recent developments ...

Authorship attribution stems from the idea that one can use a text to derive useful conclusions about its author. It is a rather old idea, that has recently gained momentum due to the major technological leaps achieved in computer science. These leaps ...

The abundance of online information narrows our collective attention span. We address the need for automated claim validation, based on the incorporated evidence from dynamic, textually represented environments created by online news sources. We present ...

Most trust modeling research, to date, has focused on how a trustor can evaluate the trustworthiness of available trustees. In this paper, we introduce a new approach in computational trust modeling from the perspective of the trustee, in which the ...

Ever since the birth of the idea of artificial intelligence (AI), games have been helping AI research to advance. Games not only pose interesting and complex problems for AI to solve, they also offer a rich canvas for creativity and expression. This ...

Cultural Artificial Intelligence (AI) is the study, design and development of socio-technological AI systems that are implicitly or explicitly aware of the subtle and subjective complexity of human culture. Language, being a social and cultural data ...