Rytis Maskeliunas

Rytis Maskeliunas
Silesian University of Technology · Institute of Mathematics

Dr.
Expert at Horizon Europe Programme Committee, configuration ‘Digital, Industry and Space’

About

259
Publications
203,440
Reads
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2,618
Citations
Introduction
Rytis Maskeliunas currently works as Invited Professor, at the Institute of Mathematics, Silesian University of Technology. Rytis does research in next generation Collaborative Intelligence and Multimodal Human-Machine signal processing.
Additional affiliations
October 2019 - present
Silesian University of Technology
Position
  • Professor
February 2017 - present
Kaunas University of Technology
Position
  • Professor
September 2013 - January 2017
Kaunas University of Technology
Position
  • Professor (Associate)

Publications

Publications (259)
Article
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We adopt Bidirectional Long Short-Term Memory (BiLSTM) neural network and Wavelet Scattering Transform with Support Vector Machine (WST-SVM) classifier for detecting speech impairments of patients at the early stage of central nervous system disorders (CNSD). The study includes 339 voice samples collected from 15 subjects: 7 patients with early sta...
Article
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We present a model for digital neural impairment screening and self-assessment, which can evaluate cognitive and motor deficits for patients with symptoms of central nervous system (CNS) disorders, such as mild cognitive impairment (MCI), Parkinson's disease (PD), Huntington's disease (HD), or dementia. The data was collected with an Android mobile...
Article
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With the majority of research, in relation to 3D object reconstruction, focusing on single static synthetic object reconstruction, there is a need for a method capable of reconstructing morphing objects in dynamic scenes without external influence. However, such research requires a time-consuming creation of real world object ground truths. To solv...
Article
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Facial symmetry is a key component in quantifying the perception of beauty. In this paper, we propose a set of facial features computed from facial landmarks which can be extracted at a low computational cost. We quantitatively evaluated the proposed features for predicting perceived attractiveness from human portraits on four benchmark datasets (S...
Article
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Human posture detection allows the capture of the kinematic parameters of the human body, which is important for many applications, such as assisted living, healthcare, physical exercising and rehabilitation. This task can greatly benefit from recent development in deep learning and computer vision. In this paper, we propose a novel deep recurrent...
Article
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Federated learning (FL) is a scheme in which several consumers work collectively to unravel machine learning (ML) problems, with a dominant collector synchronizing the procedure. This decision correspondingly enables the training data to be distributed, guaranteeing that the individual device’s data are secluded. The paper systematically reviewed t...
Article
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One of the most important strategies for preventative factory maintenance is anomaly detection without the need for dedicated sensors for each industrial unit. The implementation of sound-data-based anomaly detection is an unduly complicated process since factory-collected sound data are frequently corrupted and affected by ordinary production nois...
Article
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In today’s healthcare setting, the accurate and timely diagnosis of breast cancer is critical for recovery and treatment in the early stages. In recent years, the Internet of Things (IoT) has experienced a transformation that allows the analysis of real-time and historical data using artificial intelligence (AI) and machine learning (ML) approaches...
Article
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Laryngeal carcinoma is the most common malignant tumor of the upper respiratory tract. Total laryngectomy provides complete and permanent detachment of the upper and lower airways that causes the loss of voice, leading to a patient’s inability to verbally communicate in the postoperative period. This paper aims to exploit modern areas of deep learn...
Article
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The identification of human activities from videos is important for many applications. For such a task, three-dimensional (3D) depth images or image sequences (videos) can be used, which represent the positioning information of the objects in a 3D scene obtained from depth sensors. This paper presents a framework to create foreground–background mas...
Article
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Pedestrian occurrences in images and videos must be accurately recognized in a number of applications that may improve the quality of human life. Radar can be used to identify pedestrians. When distinct portions of an object move in front of a radar, micro-Doppler signals are produced that may be utilized to identify the object. Using a deep-learni...
Article
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Low back pain is a leading cause of disability worldwide, putting a significant strain on individual sufferers, their families, and the economy as a whole. It has a significant economic impact on the global economy because of the costs associated with healthcare, lost productivity, activity limitation, and work absence. Self-management, education,...
Conference Paper
Parkinson's disease (PD) can cause many motor impairments in humans such as muscle rigidity/stiffness, hand tremors, etc., causing difficulty when interacting with computer input devices. The purpose of AQ1 this work was to classify signals obtained from keytyping using wavelet features and deep learning. We proposed a unique technique for diagnosi...
Article
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Breast cancer is a major research area in the medical image analysis field; it is a dangerous disease and a major cause of death among women. Early and accurate diagnosis of breast cancer based on digital mammograms can enhance disease detection accuracy. Medical imagery must be detected, segmented, and classified for computer-aided diagnosis (CAD)...
Article
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Current research endeavors in the application of artificial intelligence (AI) methods in the diagnosis of the COVID-19 disease has proven indispensable with very promising results. Despite these promising results, there are still limitations in real-time detection of COVID-19 using reverse transcription polymerase chain reaction (RT-PCR) test data,...
Article
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Visual perception is an important part of human life. In the context of facial recognition, it allows us to distinguish between emotions and important facial features that distinguish one person from another. However, subjects suffering from memory loss face significant facial processing problems. If the perception of facial features is affected by...
Chapter
Drivers safety is of great importance in the automotive industry today, the paramount reason for the automatic wiper controller is it helps drivers by eliminating distractions and providing overall comfort to the driver. In many recent cases, manual errors could occur from not increasing the speed of the wiper by the driver, which will as such resu...
Article
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Currently, most mask extraction techniques are based on convolutional neural networks (CNNs). However, there are still numerous problems that mask extraction techniques need to solve. Thus, the most advanced methods to deploy artificial intelligence (AI) techniques are necessary. The use of cooperative agents in mask extraction increases the effici...
Article
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Alzheimer’s disease (AD) is a neurodegenerative disease that affects brain cells, and mild cognitive impairment (MCI) has been defined as the early phase that describes the onset of AD. Early detection of MCI can be used to save patient brain cells from further damage and direct additional medical treatment to prevent its progression. Lately, the u...
Chapter
It is no longer a story that the criminal act is now the order of the day in Nigeria with the way mobile phones and network applications are being used. A lot of Nigerian citizens have in one way or the other fallen prey to this crime through online fraud, hacking into the person’s account, retrieving vital information, and the likes. It is, theref...
Chapter
The evolution and era of the latest programs and services, collectively with the enlargement of encrypted communications, make it difficult for site visitors within a safety enterprise. Virtual private networks (VPNs) are an instance of encrypted communique provider that is becoming famous, as a way for bypassing censorship in addition to gaining a...
Chapter
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Electricity plays a vital role in the developmental reform of any country (Sustainability Development Goal (SDG 7)), it is almost as important as food shelter, it’s also important to have electricity when you need it and where it is needed, in the home or business. The aim of this research is to provide energy just as it is demanded to homes and, e...
Chapter
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Recent development in agricultural techniques has led to an increase in yield and has proven to be more environmentally friendly in their applications. With the continuous increase in the world population, food demand is expected to increase simultaneously and a way to meet such immense demand is to intensify contemporary agricultural measures for...
Article
In aged people, the central vision is affected by Age-Related Macular Degeneration (AMD). From the digital retinal fundus images, AMD can be recognized because of the existence of Drusen, Choroidal Neovascularization (CNV), and Geographic Atrophy (GA). It is time consuming and costly for the ophthalmologists to monitor fundus images. A monitoring s...
Article
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The analysis and perception of behavior has usually been a crucial task for researchers. The goal of this paper is to address the problem of recognition of animal poses, which has numerous applications in zoology, ecology, biology, and entertainment. We propose a methodology to recognize dog poses. The methodology includes the extraction of frames...
Article
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Parkinson's disease (PD) is the second most common neurological disorder in the world. Nowadays, it is estimated that it affects from 2% to 3% of the global population over 65 years old. In clinical environments, a spiral drawing task is performed to help to obtain the disease's diagnosis. The spiral trajectory differs between people with PD and he...
Article
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Breast cancer detection using mammogram images at an early stage is an important step in disease diagnostics. We propose a new method for the classification of benign or malignant breast cancer from mammogram images. Hybrid thresholding and the machine learning method are used to derive the region of interest (ROI). The derived ROI is then separate...
Article
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This paper describes a unique meta-heuristic technique for hybridizing bio-inspired heuristic algorithms. The technique is based on altering the state of agents using a logistic probability function that is dependent on an agent’s fitness rank. An evaluation using two bio-inspired algorithms (bat algorithm (BA) and krill herd (KH)) and 12 optimizat...
Article
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In healthcare, a multitude of data is collected from medical sensors and devices, such as X-ray machines, magnetic resonance imaging, computed tomography (CT), and so on, that can be analyzed by artificial intelligence methods for early diagnosis of diseases. Recently, the outbreak of the COVID-19 disease caused many deaths. Computer vision researc...
Article
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Improvement of deep learning algorithms in smart agriculture is important to support the early detection of plant diseases, thereby improving crop yields. Data acquisition for machine learning applications is an expensive task due to the requirements of expert knowledge and professional equipment. The usability of any application in a real‐world se...
Article
Most research in 3D objects and its occluded region reconstruction from a single perspective focuses on object completion from a synthetically generated dataset. This leaves a major knowledge gap when morphing 3D object reconstruction from an imperfect real-world frame. As a solution to this problem, we propose a three-stage deep auto-refining adve...
Article
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Efforts to raise the bar of higher education so as to respond to dynamic societal/industry needs have led to a number of initiatives , including artificial neural network (ANN) based educational data mining (EDM) inclusive. With ANN-based EDM, humongous amount of student data in higher institutions could be harnessed for informed academic advisory...
Article
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New mobile applications need to estimate user activities by using sensor data provided by smart wearable devices and deliver context-aware solutions to users living in smart environments. We propose a novel hybrid data fusion method to estimate three types of daily user activities (being in a meeting, walking, and driving with a motorized vehicle)...
Article
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The continuous rise in skin cancer cases, especially in malignant melanoma, has resulted in a high mortality rate of the affected patients due to late detection. Some challenges affecting the success of skin cancer detection include small datasets or data scarcity problem, noisy data, imbalanced data, inconsistency in image sizes and resolutions, u...
Chapter
The frequency of credit card-based online payment frauds has increased rapidly in recent years, forcing banks and e-commerce companies to create automated fraud detection systems that perform mining on massive transaction logs. Machine learning appears to be one of the most promising techniques for detecting illegal transactions since it uses super...
Article
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Anomaly detection without employing dedicated sensors for each industrial machine is recognized as one of the essential techniques for preventive maintenance and is especially important for factories with low automatization levels, a number of which remain much larger than autonomous manufacturing lines. We have based our research on the hypothesis...
Chapter
The Alzheimer's disease (AD) is a type of dementia that affects millions of people worldwide every year and the occurrence will continue to be on the increase. The move to diagnose people suffering from AD at an earlier stage has been a daunting problem in mental health. In recent years, the advancement of deep learning in the likes of convolutiona...
Chapter
There still exists a knowledge gap in the field of computer vision in respect of posture prediction and deviation evaluation is an important metric for various medical applications, that require posture abnormality quantization. Our paper proposes a deep heuristic neural network architecture, using BlazePose as a backbone, that is capable of recons...
Article
Full-text available
A correction to this paper has been published: https://doi.org/10.1007/s10044-021-00969-x
Chapter
The use of fingerprints as a form of identification is authentic, accurate and reliable in smart phones. Due to privacy, and people feel safe that their information is secured by using locks on their android phones and can be accessed through fingerprints and other methods. An application was developed in this paper named ‘closet’ that will collect...
Article
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One of the first signs of Alzheimer’s disease (AD) is mild cognitive impairment (MCI), in which there are small variants of brain changes among the intermediate stages. Although there has been an increase in research into the diagnosis of AD in its early levels of developments lately, brain changes, and their complexity for functional magnetic reso...
Article
Full-text available
Majority of current research focuses on a single static object reconstruction from a given pointcloud. However, the existing approaches are not applicable to real world applications such as dynamic and morphing scene reconstruction. To solve this, we propose a novel two-tiered deep neural network architecture, which is capable of reconstructing sel...
Article
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Diabetic retinopathy (DR) is the main cause of blindness in diabetic patients. Early and accurate diagnosis can improve the analysis and prognosis of the disease. One of the earliest symptoms of DR are the hemorrhages in the retina. Therefore, we propose a new method for accurate hemorrhage detection from the retinal fundus images. First, the propo...
Article
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Using gestures can help people with certain disabilities in communicating with other people. This paper proposes a lightweight model based on YOLO (You Only Look Once) v3 and DarkNet-53 convolutional neural networks for gesture recognition without additional preprocessing, image filtering, and enhancement of images. The proposed model achieved high...
Article
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Manual diagnosis of skin cancer is time-consuming and expensive; therefore, it is essential to develop automated diagnostics methods with the ability to classify multiclass skin lesions with greater accuracy. We propose a fully automated approach for multiclass skin lesion segmen-tation and classification by using the most discriminant deep feature...
Article
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Face palsy has adverse effects on the appearance of a person and has negative social and functional consequences on the patient. Deep learning methods can improve face palsy detection rate, but their efficiency is limited by insufficient data, class imbalance, and high misclassification rate. To alleviate the lack of data and improve the performanc...
Chapter
Internet of things (IoT) is a disruptive technology of technical, economic and social consequence, where consumer durable goods, cars, utility components, sensors and other daily objects are linked with internet connectivity and data analysis capability tools that have changed the way, and manner people live and work. The massive deployment of IoT...
Article
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With increasing awareness of the advantages of game-based learning, there is a growing number of studies showing its application to both computer science education and sustainable development education. In this paper, we describe, with the example of the Eco JSity application, how both of these areas can be combined into a single tool. The presente...
Article
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Walking robots are considered as a promising solution for locomotion across irregular or rough terrain. While wheeled or tracked robots require flat surface like roads or driveways, walking robots can adapt to almost any terrain type. However, overcoming diverse terrain obstacles still remains a challenging task even for multi-legged robots with a...
Article
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Due to the prospect of using walking robots in an impassable environment for tracked or wheeled vehicles, walking locomotion is one of the most remarkable accomplishments in robotic history. Walking robots, however, are still being deeply researched and created. Locomotion over irregular terrain and energy consumption are among the major problems....
Chapter
The abstract should summarize the contents of the paper in short terms, i.e. 150–250 words. This article proposes a method for assessing the symptoms of tremor in patients at an early stage of Huntington’s disease (Huntington’s syndrome, Huntington’s chorea, HD). This approach includes the development of a data collection methodology using smartpho...
Chapter
Game-based learning can make educational activities more manageable and planned, and therefore contribute to the achievement of a more productive educational result. To enable adaptive and personalized learning process, the knowledge of learning game player psychological types is required. Player type can be established using a questionnaire such a...
Article
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We propose a deep learning method based on the Region Based Convolutional Neural Networks (R-CNN) architecture for the evaluation of sperm head motility in human semen videos. The neural network performs the segmentation of sperm heads, while the proposed central coordinate tracking algorithm allows us to calculate the movement speed of sperm heads...