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Search results for: DEBLURRING, DENOISING, MULTI-TASK LEARNING, VIDEO ENHANCEMENT
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Optymalizacja zasobów chmury obliczeniowej z wykorzystaniem inteligentnych agentów w zdalnym nauczaniu
PublicationRozprawa dotyczy optymalizacji zasobów chmury obliczeniowej, w której zastosowano inteligentne agenty w zdalnym nauczaniu. Zagadnienie jest istotne w edukacji, gdzie wykorzystuje się nowoczesne technologie, takie jak Internet Rzeczy, rozszerzoną i wirtualną rzeczywistość oraz deep learning w środowisku chmury obliczeniowej. Zagadnienie jest istotne również w sytuacji, gdy pandemia wymusza stosowanie zdalnego nauczania na dużą skalę...
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Constrained multi-objective optimization of compact microwave circuits by design triangulation and pareto front interpolation
PublicationDevelopment of microwave components is an inherently multi-objective task. This is especially pertinent to the design closure stage, i.e., final adjustment of geometry and/or material parameters carried out to improve the electrical performance of the system. The design goals are often conflicting so that the improvement of one normally leads to a degradation of others. Compact microwave passives constitute a representative case:...
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Visual Content Representation for Cognitive Systems: Towards Augmented Intelligence
PublicationCognitive Vision Systems have gained significant attention from academia and industry during the past few decades. One of the main reasons behind this interest is the potential of such technologies to revolutionize human life since they intend to work robustly under complex visual scenes (which environmental conditions may vary), adapting to a comprehensive range of unforeseen changes, and exhibiting prospective behavior. The combination...
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The Application of Vibration Recording and Analysis in Tribological Research on Sliding Friction
PublicationThe paper reports on a tribological research on the macroscopic manifestation and characteristics of sliding friction. The aim of the task was to measure friction in lubricated sliding contacts and test the interactions between the environment (the test rig) and the experimental friction contact. Friction-induced vibrations were observed and studied as a manifestation of the process. The typical set of velocity and force/torque...
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Approximate and analytic flow models for leak detection and identification
PublicationThe article presents a comprehensive quantitative comparison of four analytical models that, in different ways, describe the flow process in transmission pipelines necessary in the task of detecting and isolating leaks. First, the analyzed models are briefly presented. Then, a novel model comparison framework was introduced along with a methodology for generating data and assessing diagnostic effectiveness. The study presents basic...
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A Machine Learning Approach for Estimating Overtime Allocation in Software Development Projects
PublicationOvertime planning in software projects has traditionally been approached with search-based multi-objective optimization algorithms. However, the explicit solutions produced by these algorithms often lack applicability and acceptance in the software industry due to their disregard for project managers' intuitive knowledge. This study presents a machine learning model that learns the preferred overtime allocation patterns from solutions...
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Scalability of surrogate-assisted multi-objective optimization of antenna structures exploiting variable-fidelity electromagnetic simulation models
PublicationMulti-objective optimization of antenna structures is a challenging task due to high-computational cost of evaluating the design objectives as well as large number of adjustable parameters. Design speedup can be achieved by means of surrogate-based optimization techniques. In particular, a combination of variable-fidelity electromagnetic (EM) simulations, design space reduction techniques, response surface approximation (RSA) models,...
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Data augmentation for improving deep learning in image classification problem
PublicationThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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How to Design Affect-aware Educational Systems – the AFFINT Process Approach
PublicationComputer systems, that support learning processes, can adapt to the needs and states of a learner. The adaptation might directly address the knowledge deficits and most tutoring systems apply an adaptable learning path of that kind. Apart from a preliminary knowledge state, there are more factors, that influence education effectiveness and among those there are fluctuating emotional states. The tutoring systems may recognize or...
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Low-cost multi-objective optimization and experimental validation of UWB MIMO antenna
PublicationPurpose–The purpose of this paper is to validate methodologies for expedited multi-objective designoptimization of complex antenna structures both numerically and experimentally.Design/methodology/approach–The task of identifying the best possible trade-offs between theantenna size and its electrical performance is formulated as multi-objective optimization problem.Algorithmic frameworks are described for finding Pareto-optimal...
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Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions
PublicationWith the technology advancements in smart home sector, voice control and automation are key components that can make a real difference in people's lives. The voice recognition technology market continues to involve rapidly as almost all smart home devices are providing speaker recognition capability today. However, most of them provide cloud-based solutions or use very deep Neural Networks for speaker recognition task, which are...
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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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Fluid–Structure Interaction methods for the progressive anatomical and artificial aortic valve stenosis
PublicationCardiovascular system diseases, as aortic valve stenosis, are the main cause of mortality and morbidity among patients. There is still a room for enhancement of the diagnostic and therapeutic procedures, which will lead to improvement of the treatment. One of the remedies are the computer tools to support the medical diagnoses and prostheses design. The development of a procedure for modeling the aortic valves: anatomical tricuspid...
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Rapid multi-objective optimization of antennas using nested kriging surrogates and single-fidelity EM simulation models
PublicationEver increasing performance requirements make the design of contemporary antenna systems a complex and multi-stage process. One of the challenges, pertinent to the emerging application areas but also some of the recent trends (miniaturization, demands for multi-functionality, etc.), is the necessity of handling several performance figures such as impedance matching, gain, or axial ratio, often over multiple frequency bands. The...
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Thermal Image Processing for Respiratory Estimation from Cubical Data with Expandable Depth
PublicationAs healthcare costs continue to rise, finding affordable and non-invasive ways to monitor vital signs is increasingly important. One of the key metrics for assessing overall health and identifying potential issues early on is respiratory rate (RR). Most of the existing methods require multiple steps that consist of image and signal processing. This might be difficult to deploy on edge devices that often do not have specialized...
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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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Strategic Flexibility as a Mediator in Relationship between Managerial Decisions and Organizational Learning: Ambidexterity Perspective
PublicationPurpose: The purpose of the article is to determine strategic flexibility in the relationship between managerial decisions and organizational learning. The analyses are conducted in the ambidexterity convection. Design/Methodology/Approach: The study was conducted at a textile company. The company is a leader in the textile recycling industry in Poland. Empirical data were collected using the PAPI technique. The survey questionnaire...
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Advanced Ship Control Methods
PublicationThe chapter presents two main streams of research in vessel control at sea: dynamic positioning (DP) of the vessel and decision support in case of collision at sea. The control structure and basic requirements for the DP system are defined. Selected issues of automatic control of a dynamically positioned vessel are discussed. A review of advanced methods of controlling a DP ship is carried out, taking into account the tasks of...
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Quantitative risk assessment of new ship designs in damage conditions
PublicationThe paper is devoted to safety of ships in damage conditions. The novel contribution of the paper is connected with a new Multi-Task ship (MT-ship) design at the preliminary stage of design. There are a few problems at the preliminary stage that should be considered. One problem is connected with if the quantitative risk-based method is a reliable and formal method for safety assessment of such the new design (MT-ship) in damage...
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The principles of arturbain.fr for teaching sustainable urban design
PublicationThe article is an attempt to show how important it is in the contemporary education of architecture students to use an ordered repertoire of principles and concepts of a universal nature, at the same time, pointing to the new directions of solutions and answers to the problems of the 21st century. This task is implemented by the French Association L'Arturbain dans les Territoires. It is accompanied by an idea consisting in observing...
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Insights in microbiotechnology: 2022.Editorial
PublicationThis Research Topic serves as an invaluable resource for readers interested in staying updated with the latest progress and developments in the field of microbiotechnology. It spotlights the innovative research conducted by up-and-coming experts in the field, specifically emphasizing the transforming abilities of microorganisms that greatly influence the scientific community. The advent of multi-omic technologies has revolutionized microbiotechnology,...
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Effect of multi-walled carbon nanotubes properties on the photocatalytic activity of bismuth-based composites synthesised via an imidazolium ionic liquid
PublicationThe use of various types of multi-walled carbon nanotubes in the synthesis of bismuth oxybromide semiconductors via imidazolium ionic liquid was studied in detail. The effect of the MWCNT shape, specific surface area, and various diameters on the morphology, surface properties and photoactivity of the Bi-based composites has been investigated for the first time. So far, the literature has only shown the enhancement of photocatalytic...
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Comparison of the effectiveness of automatic EEG signal class separation algorithms
PublicationIn this paper, an algorithm for automatic brain activity class identification of EEG (electroencephalographic) signals is presented. EEG signals are gathered from seventeen subjects performing one of the three tasks: resting, watching a music video and playing a simple logic game. The methodology applied consists of several steps, namely: signal acquisition, signal processing utilizing z-score normalization, parametrization and...
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Method for Clustering of Brain Activity Data Derived from EEG Signals
PublicationA method for assessing separability of EEG signals associated with three classes of brain activity is proposed. The EEG signals are acquired from 23 subjects, gathered from a headset consisting of 14 electrodes. Data are processed by applying Discrete Wavelet Transform (DWT) for the signal analysis and an autoencoder neural network for the brain activity separation. Processing involves 74 wavelets from 3 DWT families: Coiflets,...
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Methodology for hospital design in architectural education
PublicationThe architecture of a hospital should be a response to strong user requirements. Recommendations on how to shape the environment of such facilities are highly complex, integrating guidelines from many fields of science. If contradictions between them exist, the designer is required to set priorities for spatial activities. This issue is particularly important during architectural education. The learning process should include projects...
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Scenario-planning solutions for waterfront flood-prone areas
PublicationThe aim of this article is to discuss the potential of applying scenario planning to achieve resilient and future-oriented solutions for flood-prone areas. The authors have proposed additions to scenario-planning processes based on the introduction of research-by-design architectural inquiries. Examined in this article is the insight into the testing of such a modified scenario-planning methodology during two courses that accompanied...
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Segmentation-Based BI-RADS ensemble classification of breast tumours in ultrasound images
PublicationBackground: The development of computer-aided diagnosis systems in breast cancer imaging is exponential. Since 2016, 81 papers have described the automated segmentation of breast lesions in ultrasound images using arti- ficial intelligence. However, only two papers have dealt with complex BI-RADS classifications. Purpose: This study addresses the automatic classification of breast lesions into binary classes (benign vs. ma- lignant)...
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Weighted Clustering for Bees Detection on Video Images
PublicationThis work describes a bee detection system to monitor bee colony conditions. The detection process on video images has been divided into 3 stages: determining the regions of interest (ROI) for a given frame, scanning the frame in ROI areas using the DNN-CNN classifier, in order to obtain a confidence of bee occurrence in each window in any position and any scale, and form one detection window from a cloud of windows provided by...
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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublicationIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...
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Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublicationMusic 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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Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing
PublicationDeveloping signal processing methods to extract information automatically has potential in several applications, for example searching for multimedia based on its audio content, making context-aware mobile applications (e.g., tuning apps), or pre-processing for an automatic mixing system. However, the last-mentioned application needs a significant amount of research to reliably recognize real musical instruments in recordings....
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Road surface roughness estimation employing integrated position and acceleration sensor
PublicationAssessment of a surface quality being an essential task for the authorities supervising the roads provides the subject of the paper. Information about riding quality of a pavement, important for drivers, both in terms of their comfort and safety is collected during experiments employing mobile sensors. The paper describes the use of a miniature position and acceleration sensor for evaluation of the roughness of the road surface....
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Robust Object Detection with Multi-input Multi-output Faster R-CNN
PublicationRecent 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
PublicationRecent 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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Selection of Visual Descriptors for the Purpose of Multi-camera Object Re-identification
PublicationA comparative analysis of various visual descriptors is presented in this chapter. The descriptors utilize many aspects of image data: colour, texture, gradient, and statistical moments. The descriptor list is supplemented with local features calculated in close vicinity of key points found automatically in the image. The goal of the analysis is to find descriptors that are best suited for particular task, i.e. re-identification...
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An automated, low-latency environment for studying the neural basis of behavior in freely moving rats
PublicationBackground Behavior consists of the interaction between an organism and its environment, and is controlled by the brain. Brain activity varies at sub-second time scales, but behavioral measures are usually coarse (often consisting of only binary trial outcomes). Results To overcome this mismatch, we developed the Rat Interactive Foraging Facility (RIFF): a programmable interactive arena for freely moving rats with multiple feeding...
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Multimedia industrial and medical applications supported by machine learning
PublicationThis article outlines a keynote paper presented at the Intelligent DecisionTechnologies conference providing a part of the KES Multi-theme Conference “Smart Digital Futures” organized in Rome on June 14–16, 2023. It briefly discusses projects related to traffic control using developed intelligent traffic signs and diagnosing the health of wind turbine mechanisms and multimodal biometric authentication for banking branches to provide...
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Fine-Tuning the Photocatalytic Activity of the Anatase {1 0 1} Facet through Dopant-Controlled Reduction of the Spontaneously Present Donor State Density
PublicationThe present study highlights the importance of the net density of charge carriers at the ground state on photocatalytic activity of the faceted particles, which can be seen as a highly underexplored problem. To investigate it in detail, we have systematically doped {1 0 1} enclosed anatase nanoparticles with Gd3+ ions to manipulate the charge carrier concentration. Furthermore, control experiments using an analogical Nb5+ doped...
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From Scores to Predictions in Multi-Label Classification: Neural Thresholding Strategies
PublicationIn this paper, we propose a novel approach for obtaining predictions from per-class scores to improve the accuracy of multi-label classification systems. In a multi-label classification task, the expected output is a set of predicted labels per each testing sample. Typically, these predictions are calculated by implicit or explicit thresholding of per-class real-valued scores: classes with scores exceeding a given threshold value...
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Open smart glasses development platform for AAL applications
PublicationThis paper describes an open platform for multi sensory electronic glasses that supports new and enhanced methods for intelligent interaction with patients, with smart objects, or to be used as new data input modalities like proximity sensor or smart textile interfaces. All the activities have been developed, investigated and evaluated within EU CHIST-ERA eGlasses project...
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How can analysts use multicriteria decision analysis?
PublicationProper decision making in multifacitated situation is very challenging task. It is especially difficult if there are many alternatives and criteria that are often contradictory. Analytical chemistry and related sciences involve many situations where decisions on complex problems are made. The support tools may be the use of MCDA (Multi-criteria Decision Analysis) algorithms. They formalize the decision process, make it transparent...
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Miniaturization-Oriented Design of Spline-Parameterized UWB Antenna for In-Door Positioning Applications
PublicationDesign of ultra-wideband antennas for in-door localization applications is a challenging task. It involves development of geometry that maintains appropriate balance between the size and performance. In this work, a topologically-flexible monopole has been generated using a stratified framework which embeds a gradient-based trust-region (TR) optimization algorithm in a meta-loop that gradually increases the structure dimensionality....
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Antenna Optimization Using Machine Learning with Reduced-Dimensionality Surrogates
PublicationIn modern times, antenna design has become more demanding than ever. The escalating requirements for performance and functionality drive the development of intricately structured antennas, where parameters must be meticulously adjusted to achieve peak performance. Often, global adjustments to geometry are necessary for optimal results. However, direct manipulation of antenna responses evaluated with full-wave electromagnetic (EM)...
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Moduł Warsztaty - narzędzie w procesie edukacji na uczelni wyższej
PublicationObecnie istnieje bardzo szeroka gama narzędzi informatycznych, które wspierają proces edukacji przy wykorzystaniu internetu na uczelniach wyższych. Wśród nieodpłatnych narzędzi powszechnie znana jest platforma Moodle. W artykule zaprezentowano jeden z jej modułów – Warsztaty. Przedstawiono jego funkcjonalność. Opisano jego zalety i wady w nauczaniu łączącym techniki online i tradycyjne na uczelni wyższej (blended-learning). W artykule...
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Performance measurements and optimization of visualization of routes traveled in the distributed dispatcher and teleinformation system for visualization of multimedia data for the Border Guard
PublicationMonitoring of country maritime border is an important task of the Border Guard. This activity can be enhanced with the use of the technology enabling gathering information from distributed sources, processing of that information and its visualization. The system presented in the paper is an advancement of the previously developed distributed map data exchange system. The added functionality allows to supplement the map data with...
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Multi Queue Approach for Network Services Implemented for Multi Core CPUs
PublicationMultiple core processors have already became the dominant design for general purpose CPUs. Incarnations of this technology are present in solutions dedicated to such areas like computer graphics, signal processing and also computer networking. Since the key functionality of network core components is fast package servicing, multicore technology, due to multi tasking ability, seems useful to support packet processing. Dedicated...
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Recent advances in assessing xenobiotics migrating from packaging material – A review
PublicationMigration of potentially toxic xenobiotics and their transformation products from packaging materials needs continuous monitoring efforts. This task requires utilizing both instrumental and biological methods as more and more novel materials reach market every year to serve consumers and reduce production costs. Unfortunately, these materials very often sneak past our legal regulations on their composition and emission of contaminants...
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Audio content analysis in the urban area telemonitoring system
PublicationArtykuł przedstawia możliwości rozwinięcie monitoringu miejskiego o automatyczną analizę dźwięku. Przedstawiono metody parametryzacji dźwięku, które możliwe są do zastosowania w takim systemie oraz omówiono aspekty techniczne implementacji. W kolejnej części przedstawiono system decyzyjny oparty na drzewach zastosowany w systemie. System ten rozpoznaje dźwięki niebezpieczne (strzał, rozbita szyba, krzyk) wśród dźwięków zarejestrowanych...
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Sensors and Sensor’s Fusion in Autonomous Vehicles
PublicationAutonomous vehicle navigation has been at the center of several major developments, both in civilian and defense applications. New technologies such as multisensory data fusion, big data processing, and deep learning are changing the quality of areas of applications, improving the sensors and systems used. New ideas such as 3D radar, 3D sonar, LiDAR, and others are based on autonomous vehicle revolutionary development. The Special...
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Neural network model of ship magnetic signature for different measurement depths
PublicationThis paper presents the development of a model of a corvette-type ship’s magnetic signature using an artificial neural network (ANN). The capabilities of ANNs to learn complex relationships between the vessel’s characteristics and the magnetic field at different depths are proposed as an alternative to a multi-dipole model. A training dataset, consisting of signatures prepared in finite element method (FEM) environment Simulia...