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Wyniki wyszukiwania dla: MULTI-TASK LEARNING, INSTRUMENT SEGMENTATION, VIDEO DEBLURRING, DENTAL MICROSCOPE, SPATIO-TEMPORAL FEATURES
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Analysis of Denoising Autoencoder Properties Through Misspelling Correction Task
PublikacjaThe paper analyzes some properties of denoising autoencoders using the problem of misspellings correction as an exemplary task. We evaluate the capacity of the network in its classical feed-forward form. We also propose a modification to the output layer of the net, which we called multi-softmax. Experiments show that the model trained with this output layer outperforms traditional network both in learning time and accuracy. We...
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Multi-instrument analysis of L-band amplitude scintillation observed over the Eastern Arabian Peninsula
PublikacjaThe study of scintillation-causing ionospheric irregularities is important to mitigate their effects on satellite communications. It is also important due to the spatial and temporal variability of these irregularities, given that their characteristics differ from one region to another. This study investigates the spatial and temporal characteristics of L1 amplitude scintillation-causing ionospheric irregularities over the Eastern...
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Examining Quality of Hand Segmentation Based on Gaussian Mixture Models
PublikacjaResults of examination of various implementations of Gaussian mix-ture models are presented in the paper. Two of the implementations belonged to the Intel’s OpenCV 2.4.3 library and utilized Background Subtractor MOG and Background Subtractor MOG2 classes. The third implementation presented in the paper was created by the authors and extended Background Subtractor MOG2 with the possibility of operating on the scaled version of...
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EXAMINING INFLUENCE OF VIDEO FRAMERATE AND AUDIO/VIDEO SYNCHRONIZATION ON AUDIO-VISUAL SPEECH RECOGNITION ACCURACY
PublikacjaThe problem of video framerate and audio/video synchronization in audio-visual speech recogni-tion is considered. The visual features are added to the acoustic parameters in order to improve the accuracy of speech recognition in noisy conditions. The Mel-Frequency Cepstral Coefficients are used on the acoustic side whereas Active Appearance Model features are extracted from the image. The feature fusion approach is employed. The...
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EXAMINING INFLUENCE OF VIDEO FRAMERATE AND AUDIO/VIDEO SYNCHRONIZATION ON AUDIO-VISUAL SPEECH RECOGNITION ACCURACY
PublikacjaThe problem of video framerate and audio/video synchronization in audio-visual speech recognition is considered. The visual features are added to the acoustic parameters in order to improve the accuracy of speech recognition in noisy conditions. The Mel-Frequency Cepstral Coefficients are used on the acoustic side whereas Active Appearance Model features are extracted from the image. The feature fusion approach is employed. The...
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Nanotubular Oxide Layer Formed on Helix Surfaces of Dental Screw Implants
PublikacjaSurface modification is used to extend the life of implants. To increase the corrosion resistance and improve the biocompatibility of metal implant materials, oxidation of the Ti-13Nb- 13Zr titanium alloy was used. The samples used for the research had the shape of a helix with a metric thread, with their geometry imitating a dental implant. The oxide layer was produced by a standard electrochemical method in an environment of...
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Examples of Original Descriptive Geometry Task Items
PublikacjaThe paper presents several descriptive geometry drawing tasks and a comprehensive approach to their evaluation. The results as the task profile include the most important features and enable interpretation of the tasks in the educational system.
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Review of Segmentation Methods for Coastline Detection in SAR Images
PublikacjaSynthetic aperture radar (SAR) images acquired by airborne sensors or remote sensing satellites contain the necessary information that can be used to investigate various objects of interest on the surface of the Earth, including coastlines. The coastal zone is of great economic importance and is also very densely populated. The intensive and increasing use of coasts and changes of coastlines motivate researchers to try to assess...
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Three-objective antenna optimization by means of kriging surrogates and domain segmentation
PublikacjaIn this paper, an optimization framework for multi-objective design of antenna structures is discussed which exploits data-driven surrogates, a multi-objective evolutionary algorithm, response correction techniques for design refinement, as well as generalized domain segmentation. The last mechanism is introduced to constrain the design space region subjected to sampling, which permits reduction of the number of training data samples...
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Comparison of Selected Neural Network Models Used for Automatic Liver Tumor Segmentation
PublikacjaAutomatic and accurate segmentation of liver tumors is crucial for the diagnosis and treatment of hepatocellular carcinoma or metastases. However, the task remains challenging due to imprecise boundaries and significant variations in the shape, size, and location of tumors. The present study focuses on tumor segmentation as a more critical aspect from a medical perspective, compared to liver parenchyma segmentation, which is the...
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Performance Evaluation of the Parallel Codebook Algorithm for Background Subtraction in Video Stream
PublikacjaA background subtraction algorithm based on the codebook approach was implemented on a multi-core processor in a parallel form, using the OpenMP system. The aim of the experiments was to evaluate performance of the multithreaded algorithm in processing video streams recorded from monitoring cameras, depending on a number of computer cores used, method of task scheduling, image resolution and degree of image content variability....
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Video content analysis in the urban area telemonitoring system
PublikacjaThe task of constant monitoring of video streams from a large number of cameras and reviewing the recordings in order to find a specified event requires a considerable amount of time and effort from the system operators and it is prone to errors. A solution to this problem is an automatic system for constant analysis of camera images being able to raise an alarm if a predefined event is detected. The chapter presents various aspects...
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Playback detection using machine learning with spectrogram features approach
PublikacjaThis 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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A Novel Method for the Deblurring of Photogrammetric Images Using Conditional Generative Adversarial Networks
PublikacjaThe visual data acquisition from small unmanned aerial vehicles (UAVs) may encounter a situation in which blur appears on the images. Image blurring caused by camera motion during exposure significantly impacts the images interpretation quality and consequently the quality of photogrammetric products. On blurred images, it is difficult to visually locate ground control points, and the number of identified feature points decreases...
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Computational Methods for Liver Vessel Segmentation in Medical Imaging: A Review
PublikacjaThe segmentation of liver blood vessels is of major importance as it is essential for formulating diagnoses, planning and delivering treatments, as well as evaluating the results of clinical procedures. Different imaging techniques are available for application in clinical practice, so the segmentation methods should take into account the characteristics of the imaging technique. Based on the literature, this review paper presents...
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Exploring Neural Networks for Musical Instrument Identification in Polyphonic Audio
PublikacjaThe purpose of this paper is to introduce neural network-based methods that surpass state-of-the-art (SOTA) models, either by training faster or having simpler architecture, while maintaining comparable effectiveness in musical instrument identification in polyphonic music. Several approaches are presented, including two authors’ proposals, i.e., spiking neural networks (SNN) and a modular deep learning model named FMCNN (Fully...
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Simulation-driven size-reduction-oriented design of multi-band antennas by means of response features
PublikacjaThis study addresses the problem of explicit size reduction of multi-band antennas by means of simulation-driven optimisation. The principal difficulty of electromagnetic (EM)-based miniaturisation of multi-band antennas is that several resonances have to be controlled independently (both in terms of their frequency allocation and depth) while attempting to reduce physical dimensions of the structure at hand. The design method...
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Machine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects
PublikacjaMachine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects Hammed A. Mojeed & Rafal Szlapczynski Conference paper First Online: 14 September 2023 161 Accesses Part of the Lecture Notes in Computer Science book series (LNAI,volume 14125) Abstract Software development project requires proper planning to mitigate risk and...
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Smart Approach for Glioma Segmentation in Magnetic Resonance Imaging using Modified Convolutional Network Architecture (U-NET)
PublikacjaSegmentation of a brain tumor from magnetic resonance multimodal images is a challenging task in the field of medical imaging. The vast diversity in potential target regions, appearance and multifarious intensity threshold levels of various tumor types are few of the major factors that affect segmentation results. An accurate diagnosis and its treatment demand strict delineation of the tumor affected tissues. Herein, we focus on...
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Analysis of metals in air particles from Gdańsk and London with EDX/EDS detectors in electron microscope
PublikacjaElectron microscopy with energy dispersive X-ray spectrometry (EDX/EDS) is the example of non-destructive analytical method for surface elemental analysis, with a potential detection limit of 0.1-0.5 wt.% for most elements. A spatial resolution <10 nm can be achieved using this technique, which provides a basis for the generation of quantitative and qualitative elemental data for individual particles. In order to obtain quantitative...
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Semantic segmentation training using imperfect annotations and loss masking
PublikacjaOne of the most significant factors affecting supervised neural network training is the precision of the annotations. Also, in a case of expert group, the problem of inconsistent data annotations is an integral part of real-world supervised learning processes, well-known to researchers. One practical example is a weak ground truth delineation for medical image segmentation. In this paper, we have developed a new method of accurate...
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Anodized multi – component titanium alloys carrying antibacterial features
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Scene Segmentation Basing on Color and Depth Images for Kinect Sensor
PublikacjaIn this paper we propose a method for segmenting single images from Kinect sensor by considering both color and depth information. The algorithm is based on a series of edge detection procedures designed for particular features of the scene objects. RGB and HSV color planes are separately analyzed in the first step with Canny edge detector, resulting in overall color edges mask. In depth images both clear boundaries and smooth...
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Features of irregularity in examples of Polish multi-family architecture constructed in 2011–2021 and nominated for the Mies van der Rohe award
PublikacjaThis article is devoted to the analysis of contemporary Polish multi-family architecture in the context of aesthetic irregularity. The research was limited to constructions from 2011–2021 and nominated for the Mies van der Rohe award as the objects with the greatest potential impact on shaping further trends. In their research, the authors focused on searching for the features of irregularities, which, in their opinion, have become...
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Virtual touchpad - video-based multimodal interface
PublikacjaA new computer interface named Virtual-Touchpad (VTP) is presented. The Virtual-Touchpad provides a multimodal interface which enables controlling computer applications by hand gestures captured with a typical webcam. The video stream is processed in the software layer of the interface. Hitherto existing video-based interfaces analyzing frames of hand gestures are presented. Then, the hardware configuration and software features...
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Medical Image Segmentation Using Deep Semantic-based Methods: A Review of Techniques, Applications and Emerging Trends
PublikacjaSemantic-based segmentation (Semseg) methods play an essential part in medical imaging analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is classified into an instance, where each class is corresponded by an instance. In particular, the semantic segmentation can be used by many medical experts in the domain of radiology, ophthalmologists, dermatologist, and image-guided radiotherapy. The authors...
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TASK CLOUD INFRASTRUCTURE IN THE CENTRE OF INFORMATICS – TRICITY ACADEMIC SUPERCOMPUTER & NETWORK
PublikacjaThe cloud solution called the TASK cloud is described. Its main components and the way of their implementation are described. Examples of deployed environments based on the cloud are also presented. Moreover, the idea of combining the cloud and big data platforms is suggested and discussed.
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The mechanisms of degradation of titanium dental implants
PublikacjaTitanium dental implants show very good properties, unfortunately there are still issues regarding material wear due to corrosion, implant loosening, as well as biological factors—allergic reactions and inflammation leading to rejection of the implanted material. In order to avoid performing reimplantation operations, changes in the chemical composition and/or modifications of the surface layer of the materials are used. This research...
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MEAN SHIFT BASED SEGMENTATION FOR BLEEDING REGIONS IN ENDOSCOPIC VIDEOS
PublikacjaWith a set of 38 manually marked bleeding regions form endoscopic videos, the authors attempted to find an optimal image segmentation method for reproducing doctor’s markup. Mean shift segmentation combined with HSV histogram segmentation were used as a segmentation method, which was then optimized by tuning the parameters of the method using global optimization algorithm. A target function for measuring the quality of segmentation was...
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Blended Learning Model for Computer Techniques for Students of Architecture
PublikacjaAbstract: The article summarizes two-year experience of implementing hybrid formula for teaching Computer Techniques at the Faculty of Architecture at the Gdansk University of Technology. Original educational e-materials, consisting of video clips, text and graphics instructions, as well as links to online resources are embedded in the university e-learning educational platform. The author discusses technical constraints associated...
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Ensembling noisy segmentation masks of blurred sperm images
PublikacjaBackground: Sperm tail morphology and motility have been demonstrated to be important factors in determining sperm quality for in vitro fertilization. However, many existing computer-aided sperm analysis systems leave the sperm tail out of the analysis, as detecting a few tail pixels is challenging. Moreover, some publicly available datasets for classifying morphological defects contain images limited only to the sperm head. This...
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublikacjaMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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Low-cost multi-objective optimization of antennas using Pareto front exploration and response features
PublikacjaIn the paper, a procedure for low-cost multi-objective optimization of antenna structures is presented. Our approach is based on exploration of the Pareto front representing the best possible trade-offs between conflicting objectives, here, the structure size and its electrical performance. Starting from the design representing the best in-band reflection level, subsequent Pareto-optimal designs are identified through local constrained...
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Universal Predictors of Dental Students’ Attitudes towards COVID-19 Vaccination: Machine Learning-Based Approach
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Nanotubular oxide layer formed on helix surfaces of dental screw implants - SEM examination
Dane BadawczeThe samples used for the research had the shape of a helix with a metric thread, with their geometry imitating a dental implant. The oxide layer was produced by a standard electrochemical method in an environment of 1M H3PO4 + 0.3 % HF for 20 min, at a constant voltage of 30 V. The oxidized samples were analyzed with a scanning electron microscope.
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Rapid Design Centering of Multi-Band Antennas Using Knowledge-Based Inverse Models and Response Features
PublikacjaAccounting for manufacturing tolerances as well as uncertainties concerning operating conditions and material parameters is one of the important yet often neglected aspects of antenna development. Appropriate quantification of uncertainties allows for estimating the fabrication yield but also to carry out robust design (e.g., yield maximization). For reliability reasons, statistical analysis should be executed at the accuracy level...
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Affect aware video games
PublikacjaIn this chapter a problem of affect aware video games is described, including such issue as: emotional model of the player, design, development and UX testing of affect-aware video games, multimodal emotion recognition and a featured review of affect-aware video games.
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Sylwester Kaczmarek dr hab. inż.
OsobySylwester Kaczmarek ukończył studia w 1972 roku jako mgr inż. Elektroniki, a doktorat i habilitację uzyskał z technik komutacyjnych i inżynierii ruchu telekomunikacyjnego w 1981 i 1994 roku na Politechnice Gdańskiej. Jego zainteresowania badawcze ukierunkowane są na: sieci IP QoS, sieci GMPLS, sieci SDN, komutację, ruting QoS, inżynierię ruchu telekomunikacyjnego, usługi multimedialne i jakość usług. Aktualnie jego badania skupiają...
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Deep Instance Segmentation of Laboratory Animals in Thermal Images
PublikacjaIn this paper we focus on the role of deep instance segmentation of laboratory rodents in thermal images. Thermal imaging is very suitable to observe the behaviour of laboratory animals, especially in low light conditions. It is an non-intrusive method allowing to monitor the activity of animals and potentially observe some physiological changes expressed in dynamic thermal patterns. The analysis of the recorded sequence of thermal...
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Robust Object Detection with Multi-input Multi-output Faster R-CNN
PublikacjaRecent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...
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Robust Object Detection with Multi-input Multi-output Faster R-CNN
PublikacjaRecent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...
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AffecTube — Chrome extension for YouTube video affective annotations
PublikacjaThe shortage of emotion-annotated video datasets suitable for training and validating machine learning models for facial expression-based emotion recognition stems primarily from the significant effort and cost required for manual annotation. In this paper, we present AffecTube as a comprehensive solution that leverages crowdsourcing to annotate videos directly on the YouTube platform, resulting in ready-to-use emotion-annotated...
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Some Security Features of Selected IoT Platforms
PublikacjaIoT (Internet of Things) is certainly one of the leading current and future trends for processing in the current distributed world. It is changing our life and society. IoT allows new ubiquitous applications and processing, but, on the other hand, it introduces potentially serious security threats. Nowadays researchers in IoT areas should, without a doubt, consider and focus on security aspects. This paper is aimed at a high-level...
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Instructor Presence in Video Lectures: Preliminary Findings From an Online Experiment
PublikacjaMotivation. Despite the widespread use of video lectures in online and blended learning environments, there is still debate whether the presence of an instructor in the video helps or hinders learning. According to social agency theory, seeing the instructor makes learners believe that s/he is personally teaching them, which leads to deeper cognitive processing and, in turn, better learning outcomes. Conversely, according to cognitive...
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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Reversible Video Stream Anonymization for Video Surveillance Systems Based on Pixels Relocation and Watermarking
PublikacjaA method of reversible video image regions of interest anonymization for applications in video surveillance systems is described. A short introduction to theanonymization procedures is presented together with the explanation of its relation to visual surveillance. A short review of state of the art of sensitive data protection in media is included. An approach to reversible Region of Interest (ROI) hiding in video is presented,...
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Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublikacjaMusic analysis and processing aims at understanding information retrieved from music (Music Information Retrieval). For the purpose of music data mining, machine learning (ML) methods or statistical approach are employed. Their primary task is recognition of musical instrument sounds, music genre or emotion contained in music, identification of audio, assessment of audio content, etc. In terms of computational approach, music databases...
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Why is TASK Quarterly a Significant Journal to Publish Your Article? —A Bibliometric Analysis of a Scientific and Technical Journal
PublikacjaA bibliometric analysis of TASK Quarterly in the years 1997-2021 in terms of various bibliometric indicators was performed to celebrate the 25th anniversary of the publication of the first issue of the journal. The number of publications and citations increased over the mentioned span of years. The leading countries in terms of the greatest number of papers published in TASK Quarterly are Poland, Italy, Germany, Ukraine, USA and...
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Deep learning based segmentation using full wavefield processing for delamination identification: A comparative study
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Improvement of Task Management with Process Models in Small and Medium Software Companies
PublikacjaSmall and medium software companies exhibit many special features that give reason for a dedicated approach to process improvement. They often cannot afford implementing maturity models or quality standards both in terms of time and money. Instead, they expect simpler solutions that can allow to run projects in more systematic and repeatable way, increase quality and knowledge management. In this paper, we present a method focused...