George Papakostas

International Hellenic University · Computer Science

Predictive maintenance (PdM) techniques can increase industrial productivity and reduce maintenance costs by predicting the remaining useful life (RUL) of complicated machines. However, PdM systems involve industrial internet of things (IIoT) devices and machine learning (ML) algorithms, which are prone to adversarial attacks. In this work, first P...

Surface damage identification implies visual inspection, which is traditionally performed manually with the bare eye. The latter is a time-consuming and error-prone process. Effectively automated inspection systems would provide sustainable solutions. The aim of this work is to investigate the development of an automated inspection system based on...

Human pose estimation (HPE) is a computer vision application that estimates human body joints from images. It gives machines the capability to better understand the interaction between humans and the environment. For this accomplishment, many HPE methods have been deployed in robots, vehicles, and unmanned aerial vehicles (UAVs). This effort raised...

Skin cancer is a senior public health issue that could profit from computer-aided diagnosis to decrease the encumbrance of this widespread disease. Researchers have been more motivated to develop computer-aided diagnosis systems because visual examination wastes time. The initial stage in skin lesion analysis is skin lesion segmentation, which migh...

The fast-paced advancement in multimedia production and exchanges over unsecured networks have led to a dire need to develop security applications. In this regard, chaos theory has much to offer, especially high-dimensional (HD) chaotic functions of fractional order. The authors propose a new symmetric, secure and robust image encryption method in...

Economic importance of wine industry globally supports the development of innovative computer vision algorithms towards precision viticulture, aiming to maximize grapes’ quantity and quality while minimizing input costs. Computer vision has the potential to provide inexpensive and non-destructive means to capture and extract precise information abo...

Fuzzy cognitive networks (FCNs) arose from traditional fuzzy cognitive maps (FCMs) to have the advantage of guaranteed convergence to equilibrium points, thus being more suitable than conventional FCMs for a variety of pattern recognition and system identification tasks. Moreover, recent developments led to FCNs with functional weights (FCNs-FW), a...

High-dimensional and multi-modal data pose an exceptional challenge in machine learning. With the number of features vastly exceeding the number of training instances, such datasets often bring established pattern recognition techniques to an awkward position: Traditional, shallow models crumble under the sheer complexity of the data, but deep neur...

This paper investigates whether deep learning architectures for semantic segmentation are capable of supporting geneticists in karyotype exporting, in a more efficient manner without requiring the intervention of humans. For the sake of experiments, 62 images from the BioImLab segmentation dataset have been adopted that contain chromosomes, nucleot...

In this paper, we built an automated machine learning (AutoML) pipeline for structure-based learning and hyperparameter optimization purposes. The pipeline consists of three main automated stages. The first carries out the collection and preprocessing of the dataset from the Kaggle database through the Kaggle API. The second utilizes the Keras-Baye...

National flags are the most recognizable symbols of the identity of a country. Similarities between flags may be observed due to cultural, historical, or ethical connections between nations, because they may be originated from the same group of people, or due to unrelated sharing of common symbols and colors. Although the fact that similar flags ex...

Quantum computing has been proven to excel in factorization issues and unordered search problems due to its capability of quantum parallelism. This unique feature allows exponential speed-up in solving certain problems. However, this advantage does not apply universally, and challenges arise when combining classical and quantum computing to achieve...

Communication is the most important process for a living organism. Autism is a complex developmental disorder that causes communication problems. The only way to communicate for babies is through crying, so screening analysis is an attractive approach to early diagnosis of autism to improve recovery. The aim of this paper is to explore the potentia...

The buildings in a city are of great importance. Certain historic buildings are landmarks and indicate the city’s architecture and culture. The buildings over time undergo changes because of various factors, such as structural changes, natural disaster damages, and aesthetic interventions. The form of buildings in each period is perceived and under...

This article focuses on the recent advances in the field of reinforcement learning (RL) as well as the present state–of–the–art applications in games. First, we give a general panorama of RL while at the same time we underline the way that it has progressed to the current degree of application. Moreover, we conduct a keyword analysis of the literat...

Machine learning (ML) algorithms due to their outstanding performances are being extensively used in applications covering several different domains. Recently, the increased growth of cloud services provided training infrastructures for complex ML models able to deal with big data, resulting in the enhancement of ML as a Service (MLaaS). Toward thi...

Globalization of markets involves new strategies and price policies from professionals that contribute to global competitiveness. Airline companies are changing tickets’ prices very often considering a variety of factors based on their proprietary rules and algorithms that are searching for the most suitable price policy. Recently, Artificial Intel...

Plant diseases are one of the primary causes of decreased agricultural production quality and quantity. With ongoing changes in plant structure and cultivation techniques, new diseases are constantly arising on plant leaves. Thus, accurate classification and detection of plant leaf diseases in their early stages will limit the spread of the infecti...

Knowing some characteristics of an unknown user is useful information for security and commercial purposes. One of the acquired characteristics is the user’s native language, and its recognition can be achieved with data derived from the text he/she types, since text is the most widespread means of communication between Internet users. Keystroke dy...

Difficulties with social interaction characterise children with Autism Spectrum Disorders and have a negative impact in their everyday life. Integrating a social-humanoid robot within the standard clinical treatment has been proven promising. The main aim of this randomised controlled study was to evaluate the effectiveness of a robot-assisted psyc...

One of the essential layers in most Convolutional Neural Networks (CNNs) is the pooling layer, which is placed right after the convolution layer, effectively downsampling the input and reducing the computational power required. Different pooling methods have been proposed over the years, each with its own advantages and disadvantages, rendering the...

Medical discoveries mainly depend on the capability to process and analyze biological datasets, which inundate the scientific community and are still expanding as the cost of next-generation sequencing technologies is decreasing. Deep learning (DL) is a viable method to exploit this massive data stream since it has advanced quickly with there being...

Nowadays, an important topic that is considered a lot is how to integrate Machine Learning (ML) to cloud resources management. In this study, our goal is to explore the most important cloud resources management issues that have been combined with ML and which present many promising results. To accomplish this, we used chronological charts based on...

In the past years, deep neural networks (DNNs) have become popular in many disciplines such as computer vision (CV). One of the most important challenges in the CV area is Medical Image Analysis (MIA). However, adversarial attacks (AdAs) have proven to be an important threat to vision systems by significantly reducing the performance of the models....

Cracks can occur on different surfaces such as buildings, roads, aircrafts, etc. The manual inspection of cracks is time-consuming and prone to human error. Machine vision has been used for decades to detect defects in materials in production lines. However, the detection or segmentation of cracks on a randomly textured surface, such as marble, has...

The global expansion of the sports betting industry has brought the prediction of outcomes of sport events into the foreground of scientific research. In this work, soccer outcome prediction methods are evaluated, focusing on the Greek Super League. Data analysis, including data cleaning, Sequential Forward Selection (SFS), feature engineering meth...

Biometrics have been used to identify humans since the 19th century. Over time, these biometrics became 3D. The main reason for this was the growing need for more features in the images to create more reliable identification models. This work is a comprehensive review of 3D biometrics since 2011 and presents the related work, the hardware used and...

The representation of the physical world is an issue that concerns the scientific community studying computer vision, more and more. Recently, research has focused on modern techniques and methods of photogrammetry and stereoscopy with the aim of reconstructing three-dimensional realistic models with high accuracy and metric information in a short...

An important factor in the successful marketing of natural ornamental rocks is providing sets of tiles with matching textures. The market price of the tiles is based on the aesthetics of the different quality classes and can change according to the varying needs of the market. The classification of the marble tiles is mainly performed manually by e...

Energy consumption forecasting is essential for efficient resource management related to both economic and environmental benefits. Forecasting can be implemented through statistical analysis of historical data, application of Artificial Intelligence (AI) algorithms, physical models, and more, and focuses on two directions: the required load for a s...

In the past years, Deep Neural Networks (DNNs) have become popular in many disciplines such as Computer Vision (CV), and the evolution of hardware has helped researchers to develop many powerful Deep Learning (DL) models to deal with several problems. One of the most important challenges in the CV area is Medical Image Analysis. However, adversaria...

A very important task of Natural Language Processing is text categorization (or text classification), which aims to automatically classify a document into categories. This kind of task includes numerous applications, such as sentiment analysis, language or intent detection, heavily used by social-/brand-monitoring tools, customer service, and the v...

Motor Imagery Brain Computer Interfaces (MI-BCIs) are systems that receive the users’ brain activity as an input signal in order to communicate between the brain and the interface or an action to be performed through the detection of the imagination of a movement. Brainwaves’ features are crucial for the performance of the interface to be increased...

This paper presents the results of the survey that was conducted during 2018 in four countries: Bulgaria, Greece, Bosnia and Herzegovina and Croatia. The survey is a part of activities within the project “Increasing the well being of the population by RObotic and ICT based iNNovative education” (RONNI), funded by the Danube Strategic Project Fund (...

Tsakalidou, Viktoria N.Mitsou, PavlinaPapakostas, George A.Computer science and specifically the sector of artificial intelligence, after many years of basic research, has recently developed the computer’s interpretation of medical images that outperforms the human’s in specific areas. The most prevalent diseases worldwide are the dermatological. D...

Automatic navigation of agricultural machinery is an important aspect of Smart Farming. Intelligent agricultural machinery applications increasingly rely on machine vision algorithms to guarantee enhanced in-field navigation accuracy by precisely locating the crop lines and mapping the navigation routes of vehicles in real-time. This work presents...

This paper presents the fsmpy Python library for the implementation of any type of measures and comparisons of different types of fuzzy sets, as well as other important and useful utilities and algorithms. In this paper, we analyze the motivation behind its implementation, the design principles followed, the implemented modules of the library and i...

Recent years have witnessed the proliferation of social robots in various domains including special education. However, specialized tools to assess their effect on human behavior, as well as to holistically design social robot applications, are often missing. In response, this work presents novel tools for analysis of human behavior data regarding...

During the last decade, there has been an increased interest in research on the use of social robots in education, both in typical education as well as in special education. Despite the demonstrated advantages of robot-assisted tutoring in typical education and the extensive work on robots in supporting autism therapy-related scenarios, little work...

This paper is an overview of the Machine Learning Operations (MLOps) area. Our aim is to define the operation and the components of such systems by highlighting the current problems and trends. In this context, we present the different tools and their usefulness in order to provide the corresponding guidelines. Moreover, the connection between MLOp...

Over the last decades, images have become an important source of information in many domains, thus their high quality has become necessary to acquire better information. One of the important issues that arise is image denoising, which means recovering a signal from inaccurately and/or partially measured samples. This interpretation is highly correl...

Rheumatoid arthritis (RA) is a systemic autoimmune disease that preferably affects small joints. As the well-timed diagnosis of the disease is essential for the treatment of the patient, several works have been conducted in the field of deep learning to develop fast and accurate automatic methods for RA diagnosis. These works mainly focus on medica...

This work highlights the most recent machine vision methodologies and algorithms proposed for estimating the ripening stage of grapes. Destructive and non-destructive methods are overviewed for in-field and in-lab applications. Integration principles of innovative technologies and algorithms to agricultural agrobots, namely, Agrobots, are investiga...

Representation and classification of color texture generate considerable interest within the field of computer vision. Texture classification is a difficult task that assigns unlabeled images or textures to the correct labeled class. Some key factors such as scaling and viewpoint variations and illumination changes make this task challenging. In th...

Over the last decades, images have become an important source of information in many domains, thus their high quality has become necessary to acquire better information. One of the important issues that arise is image denoising, which means recovering a signal from inaccurately and/or partially measured samples. This interpretation is highly correl...

Social robots keep proliferating. A critical challenge remains their sensible interaction with humans, especially in real world applications. Hence, computing with real world semantics is instrumental. Recently, the Lattice Computing (LC) paradigm has been proposed with a capacity to compute with semantics represented by partial order in a mathemat...

Identifying the provenance of volcanic rocks can be essential for improving geological maps in the field of geology and providing a tool for the geochemical fingerprinting of ancient artifacts like millstones and anchors in the field of geoarchaeology. This study examines a new approach to this problem by using machine learning algorithms (MLAs). I...

Ripeness estimation of fruits and vegetables is a key factor for the optimization of field management and the harvesting of the desired product quality. Typical ripeness estimation involves multiple manual samplings before harvest followed by chemical analyses. Machine vision has paved the way for agricultural automation by introducing quicker, cos...

In the past years, deep neural networks (DNN) have become popular in many disciplines such as computer vision (CV), natural language processing (NLP), etc. The evolution of hardware has helped researchers to develop many powerful Deep Learning (DL) models to face numerous challenging problems. One of the most important challenges in the CV area is...

Morphological operators are nonlinear transformations commonly used in image processing. Their theoretical foundation is based on lattice theory, and it is a well-known result that a large class of image operators can be expressed in terms of two basic ones, the erosions and the dilations. In practice, useful operators can be built by combining the...

Cognitive Behavioral Therapy (CBT) has been proven an effective tool to address anger and anxiety issues in children and adolescents with Autism Spectrum Disorders (ASD). Robot-enhanced therapy has been used in psychosocial and educational interventions for children with ASD with promising results. Whenever CBT-based techniques were incorporated in...

Fire hazard is a condition that has potentially catastrophic consequences. Artificial intelligence, through Computer Vision, in combination with UAVs has assisted dramatically to identify this risk and avoid it in a timely manner. This work is a literature review on UAVs using Computer Vision in order to detect fire. The research was conducted for...