Chairi Kiourt

• PhD in Artificial intelligence
• Principal Researcher at Athena Research and Innovation Center In Information Communication & Knowledge Technologies

Small cultural institutions play a vital role in preserving and promoting cultural heritage. To ensure their long-term viability and growth, these institutions must undergo a digital transformation. However, they often face significant challenges due to limited resources and a lack of technical expertise. This paper delves into the crucial role of...

This CIDACC dataset was created to determine the cell population of Chlorella vulgaris microalga during cultivation. Chlorella vulgaris has diverse applications, including use as food supplement, biofuel production, and pollutant removal. High resolution images were collected using a microscope and annotated, focusing on computer vision and machine...

The intersection of COVID-19 and pulmonary embolism (PE) has posed unprecedented challenges in medical diagnostics. The critical nature of PE and its increased incidence during the pandemic underline the need for improved detection methods. This study evaluates the effectiveness of advanced deep learning techniques in enhancing PE detection in post...

Black spot identification, a spatiotemporal phenomenon, involves analyzing the geographical location and time-based occurrence of road accidents. Typically, this analysis examines specific locations on road networks during set time periods to pinpoint areas with a higher concentration of accidents, known as black spots. By evaluating these problem...

Black spot identification, a spatiotemporal phenomenon, involves analysing the geographical location and time-based occurrence of road accidents. Typically, this analysis examines specific locations on road networks during set time periods to pinpoint areas with a higher concentration of accidents, known as black spots. By evaluating these problem...

Plant phenotyping refers to a quantitative description of the plant's properties, however in image-based phenotyping analysis, our focus is primarily on the plant's anatomical, ontogenetical and physiological properties. This technique reinforced by the success of Deep Learning in the field of image based analysis is applicable to a wide range of r...

Plant phenotyping refers to a quantitative description of the plants properties, however in image-based phenotyping analysis, our focus is primarily on the plants anatomical, ontogenetical and physiological properties.This technique reinforced by the success of Deep Learning in the field of image based analysis is applicable to a wide range of rese...

The sunken city of old Epidaurus is one of the most significant archaeological sea-sites on the east coast of Peloponnese, Greece. Remains of ancient buildings are preserved in the area with a Roman villa located about 50m from the coast, the most notable of them. The site is attracting tourists and researchers from various scientific domains, such...

Tourism is a phenomenon that dates back to ancient times. Ancient Greek philosophers recognised, adopted, and promoted the concept of rest-based tourism. Ecotourism is a particular type of tourism that connects with activities that take place in nature, without harming it, along with the herbal and animal wealth. According to estimates, the global...

Haptic prohibition is one of the most common limitations when interacting with museum artefacts. This restriction aims quite logically at preventing damages while safeguarding the integrity of the cultural reserve, which is primarily characterised by its uniqueness. Nevertheless, in cases where museum visitors are visually impaired, the inability t...

Plant identification from images has become a rapidly developing research field in computer vision and is particularly challenging due to the morphological complexity of plants. The availability of large databases of plant images, and the research advancements in image processing, pattern recognition and machine learning, have resulted in a number...

The main objective of this work is to utilize state-of-the-art deep learning approaches for the identification of pulmonary embolism in CTPA-Scans for COVID-19 patients, provide an initial assessment of their performance and, ultimately, provide a fast-track prototype solution (system). We adopted and assessed some of the most popular convolutional...

The identification of ancient coins is a time consuming and complex task with huge experience demands. The analysis of numismatic evidence through patterns detection executed by Machine Learning methods has started to be recognized as approaches that can provide archaeologists with a wide range of tools, which, especially in the fields of numismati...

The last decades, crowd simulation for crisis management is highlighted as an important topic of interest for many scientific fields. As the continuous evolution of computational resources increases, along with the capabilities of Artificial Intelligence, the demand for better and more realistic simulation has become more attractive and popular to...

Image content prediction with novel deep learning approaches is a hot research topic for many scientific disciplines. Image-based food types recognition and their ingredients is a particularly challenging task, since food dishes are typically deformable objects, usually including complex semantics, which makes the task of defining their structure v...

Exploiting extended reality technologies in laboratory training enhances both teaching and learning experiences. It complements the existing traditional learning/teaching methods related to science, technology, engineering, arts and mathematics. In this work, we use extended reality technologies to create an interactive learning environment with dy...

With the advent of the computational technologies (Graphics Processing Units - GPUs) and Machine Learning, the research domain of crowd simulation for crisis management has flourished. Along with the new techniques and methodologies that have been proposed all those years, aiming to increase the realism of crowd simulation, several crisis simulatio...

Automatic image-based food recognition is a particularly challenging task. Traditional image analysis approaches have achieved low classification accuracy in the past, whereas deep learning approaches enabled the identification of food types and their ingredients. The contents of food dishes are typically deformable objects, usually including compl...

Gastronomy is increasingly becoming a decisive flavour of tourists’ experience. Tourists’ gastronomic experience could be significantly enhanced by AI tools that provide image-based dish recognition and menu translation, thus covering the basic needs of tourists during a visit that involves culinary experiences. This paper presents and discusses so...

The last few decades, crowd simulation for crisis management is highlighted as an important topic of interest for many scientific fields. As the continues evolution of computational resources increases, along with the capabilities of Artificial Intelligence, the demand for better and more realistic simulation has become more attractive and popular...

Automatic image-based food recognition is a particularly challenging task. Traditional image analysis approaches have achieved low classification accuracy in the past, whereas deep learning approaches enabled the identification of food types and their ingredients. The contents of food dishes are typically deformable objects, usually including compl...

This article focuses on important factors in the creation of enhanced personalised experiences in virtual environments for cultural heritage applications, especially those targeting virtual museums and exhibitions. Some of the most important factors relating to personalised virtual museums that relate to intelligent content and user modelling in vi...

One of the most challenging problems in the simulation of real environments is to generate worlds that appear realistic and more attractive. It becomes increasingly challenging when the simulated environment focuses on minors (students), because the young generation has high demands on simulation systems due to their experience in computer gaming....

One of the most challenging tasks in cross reality environment simulations is the generation of realistic and attractive worlds. The continuous evolution of computer game industry has a dramatic effect on such tasks as younger generations have higher expectations and demands in terms of realism. Virtual, Augmented, and mixed reality-based museums a...

Numerous software solutions implementing the structure-from-motion/multi-view stereo (SFM/MVS) 3D reconstruction approach have been made available over the last two decades. Hence, enabling the production of high quality, in terms of geometry and colour information, 3D objects using solely unordered image sequences depicting a static scene or objec...

As an integral part of archaeology, archaeometry, employs standard laboratory techniques and ICT tools to examine and analyze art and archaeological materials. Most students involved with cultural heritage and Αrchaeology have a background in the arts or humanities and a minimal, if any, training in the principles and techniques of most natural and...

One of the most challenging tasks in Extended Reality based environments is the creation of realistic, interactive and attractive simulation with personalised content, without overlooking the main purpose of the system, which, in our case, is education. This paper introduces the XRLabs platform, which is an Extended Reality platform to assist in th...

Avery effective and promising approach to simulate real-life conditions in multi-agent virtual environments with intelligent agents is to introduce social parameters and dynamics. Introduction of social parameters in such settings reshapes the overall performance of the synthetic agents, so a new challenge of reconsidering the methods to assess age...

The digital cultural heritage field has been developing in parallel with modern archaeology by collecting and storing data from all aspects of field work, from excavations to virtual representations and to exhibitions, and by transforming data into knowledge and new services, ranging from supporting scientists to offering edutainment content. As an...

Agent based simulation of social organizations, via the investigation of agents’ training and learning tactics and strategies, has been inspired by the ability of humans to learn from social environments which are rich in agents, interactions and partial or hidden information. Such richness is a source of complexity that an effective learner has to...

Virtual laboratories are the new online educational trend for communicating to students practical skills of science. In this paper we report on a comparison of techniques for familiarizing distance learning students with a 3D virtual biology laboratory, in order to prepare them for their microscopy experiment in their physical wet lab. Initial trai...

This article focuses on important factors in the creation of enhanced personalised experiences in virtual environments for cultural heritage applications, especially those targeting virtual museums and exhibitions. Some of the most important factors relating to personalised virtual museums that relate to intelligent content and user modelling in vi...

Coupling culture and education has attracted significant attention and pushed towards the replacement of the typical STEM model into STEAM. An effective integration of culture in the everyday educational practice, empowered by game-based storytelling has already shown great potential in transforming the way people are exposed to and grasp knowledge...

This paper focuses on the integration of artificial intelligence methods in multi-agent virtual environments for cultural heritage applications and especially virtual museums and exhibitions. Multi-agent systems are considered here as being autonomous social organizations capable of developing dynamic personalized virtual environments. In this resp...

Agent based simulation of social organizations, via the investigation of agents' training and learning tactics and strategies, has been inspired by the ability of humans to learn from social environments which are rich in agents, interactions and partial or hidden information. Such richness is a source of complexity that an effective learner has to...

Numerous software solutions that implement the Structure-from-Motion/Multi-View Stereo (SfM/MVS) 3D reconstruction approach have been made available during the last decade. These allow the production of high quality in terms of geometry and colour information 3D models with the use of unordered image collections that depict a static scene or object...

One of the most challenging problems in the simulation of real environments is to generate worlds that appear realistic and more attractive. It becomes increasingly challenging when the simulated environment focuses on minors (students), because the young generation has high demands on simulation systems due to their experience in computer gaming....

This paper investigates the performance of synthetic agents in playing and learning scenarios in a turn-based zero-sum game and highlights the ability of opponent-based learning models to demonstrate competitive playing performances in social environments. Synthetic agents are generated based on a variety of combinations of some key parameters, suc...

This paper investigates the learning progress of inexperienced agents in competitive game playing social environments. We aim to determine the effect of a knowledgeable opponent on a novice learner. For that purpose, we used synthetic agents whose playing behaviors were developed through diverse reinforcement learning set-ups, such as exploitation-...

Open linked data technologies pave the way towards the semantic Web of the future by a) exploiting the abundance in data availability, b) enhancing the continuing application developments in the Web and computer technologies, c) increasing the availability of game engines towards an expansion of techniques and d) bridging culture and education with...

he evolving technologies of the game engines and the Web have reached a level of maturity that enables them to contribute significantly to the long-celebrated blending of culture and education with gaming. In this work, we present DynaMus, an innovative fully dynamic Web-based virtual museum framework that relies entirely on users’ creativity and o...

The introduction of social dynamics in multi-agent environments with synthetic agents is an effective way to simulate real-life conditions. Nowadays there is a trend towards the integration of social dynamics in multi-agent virtual environments to better assess the performance of synthetic agents in competitive situations. This assessment is usuall...

We examine how synthetic agents interact in social environments employing a variety of agent τraining strategies against diverse opponents. Such agent training and playing methods indicate that quality playing relies more on the correct set-up of the learning mechanism than on experience. The experimentation provides valuable insight into the poten...

Modern artificial intelligence approaches study game-playing agents in multi-agent social environments, in order to better simulate the real world playing be-haviors; these approaches have already produced promising results. In this paper we present the results of applying human rating systems for competitive games with social activity, to evaluate...

Abstract: The simulation of societies requires vast amounts of computing resources, which must be managed over distributed or high performance computing infrastructures to provide for cost-effective experimentation. To that end, this paper presents a novel platform for the segmentation and management of social simulation experiments in game-playing...

Abstract—Continuous developments in the web and computer technologies along with an increasing availability of game engines contribute to an expansion of techniques that bridge culture and education with gaming. In addition, open linked data technologies pave the way towards the semantic web of the future by exploiting the abundance in data availab...

Abstract The continuous development of web services and computer infrastructures complemented by the increasing availability of game development software engines, contribute to an on-going expansion in the release of serious games (SG) in diverse areas, ranging from entertainment, cultural heritage (CH), education, artificial intelligence (AI),...

Abstract Technological innovations have rapidly increased over the recent years as well as e-learning usage and thus museums have increased e-learning investment in order to adapt their services in a better and more efficient way for their visitors. While museums offer a diverse range of personal digital collections systems on their websites it...

This work introduces a novel, modular, layered web based platform for managing machine learning experiments on grid-based High Performance Computing infrastructures. The coupling of the communication services offered by the grid, with an administration layer and conventional web server programming, via a data synchronization utility, leads to the s...

In this paper we present a novel architecture for streamlining human expert management for a multi agent system deployed at the grid with the objective of investigating social learning. The coupling of the communication services offered by the grid, with an administration layer and conventional web server programming, via a data synchronization uti...

The development of a novel Multi-Agent-Based Social Simulation (MABS) platform is undertaken after considering the advantages and disadvantages of existing platforms. We study their adaptability and usage in an existing strategy board game and attempt to model tournaments in social environments. To facilitate this experimentation, we arrive at the...

In this work we discuss Social Reinforcement Learning on self-trained agents. We simulate social learning by implementing a tournament on an existing board game that utilizes reinforcement learning for playing and learning. The socially trained agents are compared to self-trained agents and their superior performance is noted. The findings and the...

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