Search results for: SUPER RESOLUTION, DEEP LEARNING, THERMAL IMAGERY, OBJECT DETECTION
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Moving object detection and tracking for the purpose of multimodal surveillance system in urban areas
PublicationBackground subtraction method based on mixture of Gaussians was employed to detect all regions in a video frame denoting moving objects. Kalman filters were used for establishing relations between the regions and real moving objects in a scene and for tracking them continuously. The objects were represented by rectangles. The objects coupling with adequate regions including the relation of many-to-many was studied experimentally...
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Deep learning approach for delamination identification using animation of Lamb waves
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OmicSelector: automatic feature selection and deep learning modeling for omic experiments
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Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition
Publicationconvolutional neural network (CNN) which is a class of deep, feed-forward artificial neural network. We decided to analyze audio signal feature maps, namely spectrograms, linear and Mel-scale cepstrograms, and chromagrams. The choice was made upon the fact that CNN performs well in 2D data-oriented processing contexts. Feature maps were employed in the Lithuanian word recognition task. The spectral analysis led to the highest word...
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Autonomous pick-and-place system based on multiple 3Dsensors and deep learning
PublicationGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Deep learning approach on surface EEG based Brain Computer Interface
PublicationIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Using deep learning to increase accuracy of gaze controlled prosthetic arm
PublicationThis paper presents how neural networks can be utilized to improve the accuracy of reach and grab functionality of hybrid prosthetic arm with eye tracing interface. The LSTM based Autoencoder was introduced to overcome the problem of lack of accuracy of the gaze tracking modality in this hybrid interface. The gaze based interaction strongly depends on the eye tracking hardware. In this paper it was presented how the overall the...
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High resolution XPS analysis of BDD electrode functionalization steps towards SARS-CoV-2 detection
Open Research DataThis dataset contains the results of the high-resolution XPS analyses of a set of boron-doped diamond (BDD) electrodes after consecutive functionalization steps toward anchoring of a receptor capable of SARS-CoV-2 virus detection. The analysis was carried out in the binding energy range of C1s, N1s, O1s, Ni2p3/2. The measurements were carried out on...
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The use of machine learning for face regions detection in thermograms
PublicationThe aim of this study is to analyse the methods of detecting characteristic points of the face in thermographic images. As part of the implementation an extensive analysis of scientific publications covering similar issues both for the analysis of images made in visible light and thermographic images was carried out. On the basis of this analysis, 3 models were selected and then they were implemented and tested on the basis of...
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High-Resolution, Broad-Range Detection Setup for Polarimetric Optical Fiber Sensors
PublicationA common-path polarization interferometer using a Wollaston prism and an area detector for the measurement of retardation or optical path difference is presented. Employing a moderate-resolution 1280 by 1024 pixel monochrome camera, it offers a measurement range of approximately 780 radians at 830 nm and 1350 radians at 515 nm while maintaining a high measurement resolution. Retardation introduced by a zero-order waveplate or a...
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Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance
PublicationMachine learning and Artificial Intelligence have grown significant attention from industry and academia during the past decade. The key reason behind interest is such technologies capabilities to revolutionize human life since they seamlessly integrate classical networks, networked objects and people to create more efficient environments. In this paper, the Knowledge Representation technique of Set of Experience...
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Low-Cost and Highly-Accurate Behavioral Modeling of Antenna Structures by Means of Knowledge-Based Domain-Constrained Deep Learning Surrogates
PublicationThe awareness and practical benefits of behavioral modeling methods have been steadily growing in the antenna engineering community over the last decade or so. Undoubtedly, the most important advantage thereof is a possibility of a dramatic reduction of computational expenses associated with computer-aided design procedures, especially those relying on full-wave electromagnetic (EM) simulations. In particular, the employment of...
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Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
PublicationThe solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen...
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Improved estimation of dynamic modulus for hot mix asphalt using deep learning
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublicationGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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The detection of Alternaria solani infection on tomatoes using ensemble learning
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<title>Ultrahigh-resolution detection techniques for biomedical applications of optical coherent tomography</title>
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Thermal Instability of Choline Chloride-Based Deep Eutectic Solvents and Its Influence on Their Toxicity─Important Limitations of DESs as Sustainable Materials
PublicationDeep eutectic solvents (DESs) have become a hot topic in many branches of science due to their remarkable properties. They have been studied in a wide variety of applications. In particular, choline chloride (ChCl)-based DESs are one of the most commonly used representatives of these fluids. Nevertheless, in order to apply DESs in some fields, it is essential to guarantee their stability, reusability, and biocompatibility. In this...
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Deep learning model for automated assessment of lexical stress of non-native english speakers
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Prediction of Sorption Processes Using the Deep Learning Methods (Long Short-Term Memory)
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Wireless Link Selection Methods for Maritime Communication Access Networks—A Deep Learning Approach
PublicationIn recent years, we have been witnessing a growing interest in the subject of communication at sea. One of the promising solutions to enable widespread access to data transmission capabilities in coastal waters is the possibility of employing an on-shore wireless access infrastructure. However, such an infrastructure is a heterogeneous one, managed by many independent operators and utilizing a number of different communication...
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublicationMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Deep learning based segmentation using full wavefield processing for delamination identification: A comparative study
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Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublicationBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
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The motion influence on respiration rate estimation from low-resolution thermal sequences during attention focusing tasks
PublicationGlobal aging has led to a growing expectancy for creating home-based platforms for indoor monitoring of elderly people. A motivation is to provide a non-intrusive technique, which does not require special activities of a patient but allows for remote monitoring of elderly people while assisting them with their daily activities. The goal of our study was to evaluate motion performed by a person focused on a specific task and check...
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Towards the 4th industrial revolution: networks, virtuality, experience based collective computational intelligence, and deep learning
PublicationQuo vadis, Intelligent Enterprise? Where are you going? The authors of this paper aim at providing some answers to this fascinating question addressing emerging challenges related to the concept of semantically enhanced knowledge-based cyber-physical systems – the fourth industrial revolution named Industry 4.0.
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Experimental investigations and prediction of WEDMed surface of nitinol SMA using SinGAN and DenseNet deep learning model
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublicationThe importance of surrogate modeling techniques has been steadily growing over the recent years in high-frequency electronics, including microwave engineering. Fast metamodels are employed to speedup design processes, especially those conducted at the level of full-wave electromagnetic (EM) simulations. The surrogates enable massive system evaluations at nearly EM accuracy and negligible costs, which is invaluable in parameter...
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Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres
PublicationThe purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks....
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publication(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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Detection of thermal radiation using lanthanum-strontium-iron oxide (LSFO) bolometers
PublicationW artykule przedstawiono bolometr wykonany z tlenków lantanowo-strontowo-żelazowych zastosowany do detekcji promienowania podczerwonego. Parametry bolometru były badane za pomocą wzorcowego źródła poromieniowania o temperaturze 38°C (311 K) oddalonego od bolometru o 500 mm. W trakcie pomiarów uzyskano stosunek sygnał/szum wynoszący ok. 62 (tj. 35.9 dB). Na podstawie wyników pomiarów oszacowano dokładność pomiaru temperatury za...
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Thermal decomposition of surface compounds for the generation of small quantities of acetaldehyde. Calibration of a thermal desorption gas chromatography flame ionization detection.
PublicationW pracy opisano sposób wytwarzania niewielkich ilości acetaldehydu w procesie termicznego rozkładu związku powierzchniowego uzyskanego w wyniku chemicznej modyfikacji żelu krzemionkowego.Proces rozkładu prowadzony jest w temperaturze 130-190 stopni Celsjusza.Przedstawiono również sposób syntezy prowadzący do uzyskania odpowiedniego związku powierzchniowego.
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Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublicationThe study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain...
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Predicting Compressive Strength of Cement-Stabilized Rammed Earth Based on SEM Images Using Computer Vision and Deep Learning
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Deep Learning-based Recalibration of the CUETO and EORTC Prediction Tools for Recurrence and Progression of Non–muscle-invasive Bladder Cancer
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Detection of Cystic Fibrosis Symptoms Based on X-Ray Images Using Machine Learning- Pilot Study
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Michał Grochowski dr hab. inż.
PeopleProfessor and a Head of the Department of Intelligent Control and Decision Support Systems at Gdansk University of Technology (GUT). He is also a Member of the Board of the Digital Technologies Center of GUT. He received his M.Sc. degree in Control Engineering in 2000 from the Electrical and Control Engineering Faculty at the GUT. In 2004 he received a Ph.D. degree in Automatic Control and Robotics from this...
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AITP - AI Thermal Pedestrians Dataset
PublicationEfficient pedestrian detection is a very important task in ensuring safety within road conditions, especially after sunset. One way to achieve this goal is to use thermal imaging in conjunction with deep learning methods and an annotated dataset for models training. In this work, such a dataset has been created by capturing thermal images of pedestrians in different weather and traffic conditions. All images were manually annotated...
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Mirosław Wołoszyn dr hab. inż.
PeopleMirosław Wołoszyn born in 1963 in Gdynia. He received the M.Sc. degree in 1987, the Ph.D. degree in 1997, and the D.Sc. (‘habilitation’) degree in 2013, all from the Gdańsk University of Technology. Since 1987 he has been with the above university, where he is currently Associate Professor of Electrical Engineering. His research interests include localization and identification of ferromagnetic objects by means of the magnetometric...
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Predicting the Purchase of Electricity Prices for Renewable Energy Sources Based on Polish Power Grids Data Using Deep Learning Models for Controlling Small Hybrid PV Microinstallations
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Detection of the Oocyte Orientation for the ICSI Method Automation
PublicationAutomation or even computer assistance of the popular infertility treatment method: ICSI (Intracytoplasmic Sperm Injection) would speed up the whole process and improve the control of the results. This paper introduces a preliminary research for automatic spermatozoon injection into the oocyte cytoplasm. Here, the method for detection a correct orientation of the polar body of the oocyte is presented. Proposed method uses deep...
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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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Optimizing of target detection and tracking processes realized on consoles of passive sonar with linear towed antenna
PublicationThe long-range passive towed sonar was first modernised a few years ago. Building on operator experience over that period, a concept was developed of optimising the tasks performed by sonar operators, and improving forms of imaging to inform about object detection and support object tracking. The concept was implemented and successfully tested during ships’ manoeuvres. The optimisation of operator tasks was designed to keep listening...
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Fully Automated AI-powered Contactless Cough Detection based on Pixel Value Dynamics Occurring within Facial Regions
PublicationIncreased interest in non-contact evaluation of the health state has led to higher expectations for delivering automated and reliable solutions that can be conveniently used during daily activities. Although some solutions for cough detection exist, they suffer from a series of limitations. Some of them rely on gesture or body pose recognition, which might not be possible in cases of occlusions, closer camera distances or impediments...
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Toward Robust Pedestrian Detection With Data Augmentation
PublicationIn this article, the problem of creating a safe pedestrian detection model that can operate in the real world is tackled. While recent advances have led to significantly improved detection accuracy on various benchmarks, existing deep learning models are vulnerable to invisible to the human eye changes in the input image which raises concerns about its safety. A popular and simple technique for improving robustness is using data...
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Abdalraheem Ijjeh Ph.D. Eng.
PeopleThe primary research areas of interest are artificial intelligence (AI), machine learning, deep learning, and computer vision, as well as modeling physical phenomena (i.e., guided waves in composite laminates). The research interests described above are utilized for SHM and NDE applications, namely damage detection and localization in composite materials.
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Optimized AVHRR land surface temperature downscaling method for local scale observations: case study for the coastal area of the Gulf of Gdańsk
PublicationSatellite imaging systems have known limitations regarding their spatial and temporal resolution. The approaches based on subpixel mapping of the Earth’s environment, which rely on combining the data retrieved from sensors of higher temporal and lower spatial resolution with the data characterized by lower temporal but higher spatial resolution, are of considerable interest. The paper presents the downscaling process of the land...