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Search results for: covid-19, x-ray images, deep learning, convolutional neural network
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Video of LEGO bricks on conveyor belt - Tiles and panels
Open Research DataThe set contains videos of LEGO bricks (tiles, panels, etc.) moving on a white conveyor belt. The videos were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary camera located over the final...
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Video of LEGO bricks on conveyor belt - Bricks with studs on the side
Open Research DataThe set contains videos of LEGO bricks (bricks with studs on the side) moving on a white conveyor belt. The videos were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary camera located over...
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Video of LEGO bricks on conveyor belt - Plates with studs on the side
Open Research DataThe set contains videos of LEGO bricks (plates with studs on the side) moving on a white conveyor belt. The videos were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary camera located over...
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Video of LEGO bricks on conveyor belt - Technic Brics
Open Research DataThe set contains videos of LEGO bricks (Technic bricks) moving on a white conveyor belt. The videos were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary camera located over the final conveyor...
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Video of LEGO bricks on conveyor belt - Technic axles
Open Research DataThe set contains videos of LEGO bricks (Technic axles) moving on a white conveyor belt. The videos were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary camera located over the final conveyor...
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Ceramic composites for single-layer fuel cells
PublicationComposite materials consisting of acceptor doped lanthanum orthoniobate electrolyte phase (La0.98Ca0.02NbO4) and Li2O:NiO:ZnO semiconducting phase were synthesized. The precursor powder of La0.98Ca0.02NbO4 was prepared in nanocrystalline (mechanosynthesis) and microcrystalline (solid-state synthesis) form. The composite can be applied in a single-layer fuel cell, because of the presence of two phases acting as an anode and a cathode...
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How can Systems Thinking Help Us Handling the COVID-19 Crisis?
PublicationPurpose: COVID-19 pandemic outbreak remains one of the most influential events in the global economy over the recent years. While being primarily public health-related, it has a tremendous impact on many other aspects, such as public transport, education, and business management. Many businesses were forced to introduce rapid changes to their business models in order to survive. The aim of this paper is to show the complexity and...
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SIMULATIONS OF FRACTURE IN CONCRETE BEAMS UNDER BENDING USING A CONTINUUM AND DISCRETE APPROACH
PublicationThe paper describes two-dimensional meso-scale results of fracture in notched concrete beams under bending. Concrete was modelled as a random heterogeneous 4-phase material composed of aggregate particles, cement matrix, interfacial transitional zones and air voids. Within continuum mechanics, the simulations were carried out with the finite element method based on a isotropic damage constitutive model enhanced by a characteristic...
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Analysis of Factors Influencing the Prices of Tourist Offers
PublicationTourism is a significant branch of many world economies. Many factors influence the volume of tourist traffic and the prices of trips. There are factors that clearly affect tourism, such as COVID-19. The paper describes the methods of machine learning and process mining that allow for assessing the impact of various factors (micro, mezzo and macro) on the prices of tourist offers. The methods were used on large sets of real data...
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Video of LEGO bricks on conveyor belt - wheels, tires and caterpillars
Open Research DataThe set contains videos of LEGO bricks (wheels, tires and caterpillars) moving on a white conveyor belt. The images were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary camera located...
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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublicationFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
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Architektury klasyfikatorów obrazów
PublicationKlasyfikacja obrazów jest zagadnieniem z dziedziny widzenia komputerowego. Polega na całościowej analizie obrazu i przypisaniu go do jednej lub wielu kategorii (klas). Współczesne rozwiązania tego problemu są w znacznej części realizowane z wykorzystaniem konwolucyjnych głębokich sieci neuronowych (convolutional neural network, CNN). W tym rozdziale opisano przełomowe architektury CNN oraz ewolucję state-of-the-art w klasyfikacji...
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Using Long-Short term Memory networks with Genetic Algorithm to predict engine condition
PublicationPredictive maintenance (PdM) is a type of approach for maintenance processes, allowing maintenance actions to be managed depending on the machine's current condition. Maintenance is therefore carried out before failures occur. The approach doesn’t only help avoid abrupt failures but also helps lower maintenance cost and provides possibilities to manufacturers to manage maintenance budgets in a more efficient way. A new deep neural...
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Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention
PublicationThis paper describes two novel complementary techniques that improve the detection of lexical stress errors in non-native (L2) English speech: attention-based feature extraction and data augmentation based on Neural Text-To-Speech (TTS). In a classical approach, audio features are usually extracted from fixed regions of speech such as the syllable nucleus. We propose an attention-based deep learning model that automatically de...
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Capacity Transforming challenges into opportunities
PublicationThe Urban Initiative Laboratory (UIL) aims to upgrade the smart city concept in Gdańsk by introducing the Food-Water-Energy (FWE) nexus to the city. It was agreed in the CRUNCH international consortium that projects on different scales would be implemented in the individual countries to test the Integrated Decision Supportive system platform, which would, in principle, concern urban scale. The regular urban scale was to be researched...
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COVID-19 and digital deprivation in Poland
PublicationResearch background: The problem of digital deprivation is already known, but the COVID-19 pandemic has highlighted its negative consequences. A global change in the way of life, work and socialisation resulting from the epidemic has indicated that a basic level of digital integration is becoming necessary. During the lockdown, people were forced to use ICTs to adapt to a rapidly changing reality. Current experience with coronavirus...
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3D Hierarchical Boron-Doped Diamond-Multilayered Graphene Nanowalls as an Efficient Supercapacitor Electrode
PublicationSynthesis of stable hybrid carbon nanostructure for high-performance supercapacitor electrode with long life-cycle for electronic and energy storage devices is a real challenge. Here, we present a one-step synthesis method to produce conductive boron-doped hybrid carbon nanowalls (HCNWs), where sp2-bonded graphene has been integrated with and over a three-dimensional curved wall-like network of sp3-bonded diamond. The spectroscopic...
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Detecting Lombard Speech Using Deep Learning Approach
PublicationRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
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Karol Flisikowski dr inż.
PeopleKarol Flisikowski works as Associate Professor at the Department of Statistics and Econometrics, Faculty of Management and Economics, Gdansk University of Technology. He is responsible for teaching descriptive and mathematical statistics (in Polish and English), as well as scientific research in the field of social statistics. He has been a participant in many national and international conferences, where he has presented the results...
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How Integration of a Brain-Machine Interface and Obstacle Detection System Can Improve Wheelchair Control via Movement Image
PublicationThis study presents a human-computer interaction combined with a brain-machine interface (BMI) and obstacle detection system for remote control of a wheeled robot through movement imagery, providing a potential solution for individuals facing challenges with conventional vehicle operation. The primary focus of this work is the classification of surface EEG signals related to mental activity when envisioning movement and deep relaxation...
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Video of LEGO bricks on conveyor belt - Special Brics
Open Research DataThe set contains videos of LEGO bricks (special bricks, with additional connectors etc.) moving on a white conveyor belt. The videos were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary...
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Video of LEGO bricks on conveyor belt - Wide Brics
Open Research DataThe set contains videos of LEGO bricks (wide bricks, with each side having more than 1 stud) moving on a white conveyor belt. The videos were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary...
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Video of LEGO bricks on conveyor belt - Narrow Brics
Open Research DataThe set contains videos of LEGO bricks (narrow bricks, with on side no wider than 1 stud) moving on a white conveyor belt. The videos were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary...
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Comparison of image pre-processing methods in liver segmentation task
PublicationAutomatic liver segmentation of Computed Tomography (CT) images is becoming increasingly important. Although there are many publications in this field there is little explanation why certain pre-processing methods were utilised. This paper presents a comparison of the commonly used approach of Hounsfield Units (HU) windowing, histogram equalisation, and a combination of these methods to try to ascertain what are the differences...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublicationCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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Medical Image Dataset Annotation Service (MIDAS)
PublicationMIDAS (Medical Image Dataset Annotation Service) is a custom-tailored tool for creating and managing datasets either for deep learning, as well as machine learning or any form of statistical research. The aim of the project is to provide one-fit-all platform for creating medical image datasets that could easily blend in hospital's workflow. In our work, we focus on the importance of medical data anonimization, discussing the...
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Sathwik Prathapagiri
PeopleSathwik was born in 2000. In 2022, he completed his Master’s of Science in Biological Sciences and Bachelor’s of Engineering in Chemical Engineering in an integrated dual degree program from Birla Institute Of Technology And Science, Pilani, India. During his final year, he worked as a research intern under Dr Giri P Krishnan at Bazhenov lab, University of California San Diego school of medicine to pursue his Master’s Thesis on...
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Is This Distance Teaching Planning That Bad?
PublicationIn spring 2020, university courses were moved into the virtual space due to the Covid-19 lockdown. In this paper, we use experience from courses at Gdańsk University of Technology and ETH Zurich to identify core problems in distance teaching planning and to discuss what to do and what not to do in teaching planning after the pandemic. We conclude that we will not return to the state of (teaching) affairs that we had previously....
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LSTM-based method for LOS/NLOS identification in an indoor environment
PublicationDue to the multipath propagation, harsh indoor environment significantly impacts transmitted signals which may adversely affect the quality of the radiocommunication services, with focus on the real-time ones. This negative effect may be significantly reduced (e.g. resources management and allocation) or compensated (e.g. correction of position estimation in radiolocalisation) by the LOS/NLOS identification algorithm. This paper...
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Lonely and thinking about the past: The role of time perspectives, Big Five traits and perceived social support in loneliness of young adults during COVID-19 social distancing
PublicationBackground In Spring 2020, due to the COVID-19 pandemic, the Polish government introduced a policy of social distancing. Being apart from one’s social network had the potential to evoke feelings of loneliness. The aim of the study was to find out how time perspectives might contribute to feeling lonely during the social distancing period, controlling for Big Five personality traits and perceived social support. Participants...
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Towards Cancer Patients Classification Using Liquid Biopsy
PublicationLiquid biopsy is a useful, minimally invasive diagnostic and monitoring tool for cancer disease. Yet, developing accurate methods, given the potentially large number of input features, and usually small datasets size remains very challenging. Recently, a novel feature parameterization based on the RNA-sequenced platelet data which uses the biological knowledge from the Kyoto Encyclopedia of Genes and Genomes, combined with a classifier...
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Charge-based deep level transient spectroscopy of B-doped and undoped polycrystalline diamond films
PublicationThe undoped and B-doped polycrystalline diamond thin film was synthesized by hot filament chemical vapor deposition and microwave plasma, respectively. The structural characterization was performed by scanning electron microscopy, X-ray diffraction and Raman spectroscopy. The electrical properties of synthesized diamond layer were characterized by dc-conductivity method and charge deep level transient spectroscopy. The B-doped...
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Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublicationDeep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...
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Use of radiography images and gray level co-occurrence matrix to investigate gravitational granular flow
PublicationThe paper presents analysis of granular gravitational flow based on radiography images processing. The investigations were conducted for silo model geometry with concentric/eccentric discharging modes. The continuous X-ray radiography scans of granular material distribution, acquired during flow, were obtained by means of an especially designed model silo with rectangular bin and different settings of hopper angles. Image processing...
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Deep Features Class Activation Map for Thermal Face Detection and Tracking
PublicationRecently, capabilities of many computer vision tasks have significantly improved due to advances in Convolutional Neural Networks. In our research, we demonstrate that it can be also used for face detection from low resolution thermal images, acquired with a portable camera. The physical size of the camera used in our research allows for embedding it in a wearable device or indoor remote monitoring solution for elderly and disabled...
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Bees Detection on Images: Study of Different Color Models for Neural Networks
PublicationThis paper presents an approach to bee detection in video streams using a neural network classifier. We describe the motivation for our research and the methodology of data acquisition. The main contribution to this work is a comparison of different color models used as an input format for a feedforward convolutional architecture applied to bee detection. The detection process has is based on a neural binary classifier that classifies...
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Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction
PublicationIonic liquids (ILs) provide a promising solution in many industrial applications, such as solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to the enormous variety of their structures, uncovering or designing those with optimal attributes requires expensive and exhaustive simulations and experiments. For these reasons, searching for an efficient theoretical tool for finding the relationship...
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A new multi-process collaborative architecture for time series classification
PublicationTime series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...
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Feature Reduction Using Similarity Measure in Object Detector Learning with Haar-like Features
PublicationThis paper presents two methods of training complexity reduction by additional selection of features to check in object detector training task by AdaBoost training algorithm. In the first method, the features with weak performance at first weak classifier building process are reduced based on a list of features sorted by minimum weighted error. In the second method the feature similarity measures are used to throw away that features...
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublicationThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...
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Automatic labeling of traffic sound recordings using autoencoder-derived features
PublicationAn approach to detection of events occurring in road traffic using autoencoders is presented. Extensions of existing algorithms of acoustic road events detection employing Mel Frequency Cepstral Coefficients combined with classifiers based on k nearest neighbors, Support Vector Machines, and random forests are used. In our research, the acoustic signal gathered from the microphone placed near the road is split into frames and converted...
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Hybrid Laboratory of Radio Communication With Online Simulators and Remote Access
PublicationContribution: Two toolsets for the remote teaching of radio communication laboratory classes: 1) online simulators for individual work of students and 2) a remote access system to laboratory workstations for group work. Initial assumptions and method of implementation of both tools are presented. Background: The COVID-19 pandemic has forced a change in teaching at all levels of education. The specificity of practical classes, such...
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Balanced Spider Monkey Optimization with Bi-LSTM for Sustainable Air Quality Prediction
PublicationA reliable air quality prediction model is required for pollution control, human health monitoring, and sustainability. The existing air quality prediction models lack efficiency due to overfitting in prediction model and local optima trap in feature selection. This study proposes the Balanced Spider Monkey Optimization (BSMO) technique for effective feature selection to overcome the local optima trap and overfitting problems....
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Investigating COVID-19 active pharmaceutical ingredients (APIs) degradation using Peroxydisulfate/FeMnOx binary metal oxide/Ultrasound System
PublicationDegradation of Favipiravir using a hybrid system of peroxydisulfate, FeMnOx binary metal oxide, and ultrasound irradiation was studied. A novel catalyst was synthesized with deep eutectic solvent (DES). The effects of DES type on catalytic performance was evaluated and the catalysts were characterized using XRD, SEM, BET, XPS, and EDS. DES-based catalysts exhibited higher efficiency due to structure change, surface area enhancement...
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Hybridization of valuation procedures as a medicine supporting the real estate market and sustainable land use development during the covid-19 pandemic and afterwards
PublicationCurrently we are facing the pandemic situation that occur all over the world. Regardless the country or even the region, the negative consequences that are expected could be very big and the level of crisis is not predictable. This situation is the challenge for the real estate market as well. Due to this fact, the authors believe that there is the time when deep transformation of approaches, procedures and awareness related to...
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The trajectories of the financial crisis of companies at risk of bankruptcy
PublicationThis article concerns the assessment of the trajectory of the collapse of enterprises in Central Europe. The author has developed a model of a Kohonen artificial neural network. This model was used to determine 6 different classes of risk and was allowed to graphically determine the 5- to 10-year trajectory of going bankrupt. The study used data on 140 companies listed on the Warsaw Stock Exchange. This population was divided into...
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Aleksandra Parteka dr hab. inż.
PeopleAbout me: I am an associate professor and head of doctoral studies at the Faculty of Management and Economics, Gdansk University of Technology (GdanskTech, Poland). I got my MSc degree in Economics from Gdansk University of Technology (2003) and Universita’ Politecnica delle Marche (2005), as well as MA degree in Contemporary European Studies from Sussex University (2006, with distinction). I received my PhD in Economics...
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Playback detection using machine learning with spectrogram features approach
PublicationThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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Implementing artificial intelligence in forecasting the risk of personal bankruptcies in Poland and Taiwan
PublicationResearch background: The global financial crisis from 2007 to 2012, the COVID-19 pandemic, and the current war in Ukraine have dramatically increased the risk of consumer bankruptcies worldwide. All three crises negatively impact the financial situation of households due to increased interest rates, inflation rates, volatile exchange rates, and other significant macroeconomic factors. Financial difficulties may arise when the...
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Electrochemically Obtained TiO2/CuxOy Nanotube Arrays Presenting a Photocatalytic Response in Processes of Pollutants Degradation and Bacteria Inactivation in Aqueous Phase
PublicationTiO2/CuxOy nanotube (NT) arrays were synthesized using the anodization method in the presence of ethylene glycol and different parameters applied. The presence, morphology, and chemical character of the obtained structures was characterized using a variety of methods—SEM (scanning electron microscopy), XPS (X-ray photoelectron spectroscopy), XRD (X-ray crystallography), PL (photoluminescence), and EDX (energy-dispersive X-ray spectroscopy)....