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Wyniki wyszukiwania dla: deep learning, genetic algorithm, artificial neural networks, predictive maintenance, cost efficient maintenance
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Effects of artificial lighting on bioactivity of sweet red pepper (Capsicum annuum L.)
PublikacjaRecent studies have shown that artificial light effectively promotes the growth and development of red peppers when light spectra, intensities and duration are controlled. Cited reports deal mostly with studies involving with the growth stages of pepper. Changes in the biochemical status of plants were not studied. Therefore, this study focuses on the changes in the content of some bioactive compounds (polyphenols, flavonoids,...
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A novel architecture for e-learning knowledge assessment systems
PublikacjaAbstract. In this paper we propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. Our research proved that such architecture,while well suited for didactic content distribution systems is ill-suited for knowledge assessment...
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Active Learning Based on Crowdsourced Data
PublikacjaThe paper proposes a crowdsourcing-based approach for annotated data acquisition and means to support Active Learning training approach. In the proposed solution, aimed at data engineers, the knowledge of the crowd serves as an oracle that is able to judge whether the given sample is informative or not. The proposed solution reduces the amount of work needed to annotate large sets of data. Furthermore, it allows a perpetual increase...
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COLLABORATIVE LEARNING ENVIRONMENT FOR ENGINEERING EDUCATION (COLED)
PublikacjaCollaborative Learning Environment for Engineering Education is a European project implemented under the Erasmus + program, The main goal of 5 partners from 4 different European countries – Bulgaria, Poland, Portugal and Romania is to develop an innovative collaborative training approach, encompassing curricula related to the introduction of enterprise automation. Project activities are carried out in the period from Dctober 2018...
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Jarosław Sadowski dr hab. inż.
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Computationally-efficient design optimisation of antennas by accelerated gradient search with sensitivity and design change monitoring
PublikacjaElectromagnetic (EM) simulation tools are of primary importance in the design of contemporary antennas. The necessity of accurate performance evaluation of complex structures is a reason why the final tuning of antenna dimensions, aimed at improvement of electrical and field characteristics, needs to be based on EM analysis. Design automation is highly desirable and can be achieved by coupling EM solvers with numerical optimisation...
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Quality Evaluation of Novel DTD Algorithm Based on Audio Watermarking
PublikacjaEcho cancellers typically employ a doubletalk detection (DTD) algorithm in order to keep the adaptive filter from diverging in the presence of near-end speech signal or other disruptive sounds in the microphone signal. A novel doubletalk detection algorithm based on techniques similar to those used for audio signal watermarking was introduced by the authors. The application of the described DTD algorithm within acoustic echo cancellation...
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Computational Approaches to Modeling Artificial Emotion – An Overview of the Proposed Solutions
PublikacjaCybernetic approach to modeling artificial emotion through the use of different theories of psychology is considered in this paper, presenting a review of twelve proposed solutions: ActAffAct, FLAME, EMA, ParleE, FearNot!, FAtiMA, WASABI, Cathexis, KARO, MAMID, FCM, and xEmotion. The main motivation for this study is founded on the hypothesis that emotions can play a definite utility role of scheduling variables in the construction...
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Finding the Right Solvent: A Novel Screening Protocol for Identifying Environmentally Friendly and Cost-Effective Options for Benzenesulfonamide
PublikacjaThis study investigated the solubility of benzenesulfonamide (BSA) as a model compound using experimental and computational methods. New experimental solubility data were collected in the solvents DMSO, DMF, 4FM, and their binary mixtures with water. The predictive model was constructed based on the best-performing regression models trained on available experimental data, and their hyperparameters were optimized using a newly...
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A Novel Bitrate Adaptation Method for Heterogeneous Wireless Body Area Networks
PublikacjaIn the article, a novel bitrate adaptation method for data streams allocation in heterogeneous Wireless Body Area Networks (WBANs) is presented. The efficiency of the proposed algorithm was compared with other known algorithms of data stream allocation using computer simulation. A dedicated simulator has been developed using results of measurements in the real environment. The usage of the proposed adaptive data streams allocation...
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A Novel Bitrate Adaptation Method for Heterogeneous Wireless Body Area Networks
PublikacjaIn the article, a novel bitrate adaptation method for data streams allocation in heterogeneous Wireless Body Area Networks (WBANs) is presented. The efficiency of the proposed algorithm was compared with other known algorithms of data stream allocation using computer simulation. A dedicated simulator has been developed using results of measurements in the real environment. The usage of the proposed adaptive data streams allocation...
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Limitations of Emotion Recognition from Facial Expressions in e-Learning Context
PublikacjaThe paper concerns technology of automatic emotion recognition applied in e-learning environment. During a study of e-learning process the authors applied facial expressions observation via multiple video cameras. Preliminary analysis of the facial expressions using automatic emotion recognition tools revealed several unexpected results, including unavailability of recognition due to face coverage and significant inconsistency...
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A model, design, and implementation of an efficient multithreaded workflow execution engine with data streaming, caching, and storage constraints
PublikacjaThe paper proposes a model, design, and implementation of an efficient multithreaded engine for execution of distributed service-based workflows with data streaming defined on a per task basis. The implementation takes into account capacity constraints of the servers on which services are installed and the workflow data footprint if needed. Furthermore, it also considers storage space of the workflow execution engine and its cost....
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The role of water in deep eutectic solvent-base extraction
PublikacjaDeep eutectic solvents (DESs) are currently being used in different sectors, such as electrochemistry, electrodeposition, organic synthesis, nanoparticle preparation, bioactive compound separation, etc. Their use in analytical chemistry has only recently begun to expand. Despite the publication of a sufficient number of DES-based analytical extraction procedures, some details, such as interaction of DESwith the sample and target...
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Remarks on use of the term “deep eutectic solvent” in analytical chemistry
PublikacjaAbout 20 years ago, Abbott and co-workers researched new solvents that were based on mixtures of choline chloride with urea and carboxylic acids and that were liquid at ambient temperature. The term “deep eutectic solvent” (DES) was later adopted for similar mixtures. As DESs have a number of interesting features, they quickly attracted the attention of researchers and found application in various branches of chemical and materials...
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Traffic Modeling in IMS-based NGN Networks
PublikacjaIn the modern world the need for accurate and quickly delivered information is becoming more and more essential. In order to fulfill these requirements, next generation telecommunication networks should be fast introduced and correctly dimensioned. For this reason proper traffic models must be identified, which is the subject of this paper. In the paper standardization of IMS (IP Multimedia Subsystem) concept and IMS-based NGN...
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Learning from Mistakes. A Study on Maturity and Adaptability to Change
PublikacjaLearning culture matters; company culture must support continuous improvement. Organizational learning is a process of identifying and modifying mistakes that result from interactions between co-workers. The article aims to explore the learning power via errors, using the level of organizational maturity as a moderator. Companies need to know how organizational maturity may moderate the adaptability to change via the acceptance...
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Assessment of student language skills in an e-learning environment
PublikacjaThis article presents the role of various assessment structures that can be used in a VLE. e-Learning language courses offer tutors a wide range of traditional and computer-generated formative and summative assessment procedures and tools. They help to evaluate each student’s progress, monitor their activities and provide varied support, which comes from the tutor, the course structure and materials as well as other participants....
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Genetic Influences on Insulinemia in Normotensive Twins
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Genetic and Epigenetic Aspects of Atopic Dermatitis
PublikacjaAtopic dermatitis is a heterogeneous disease, in which the pathogenesis is associated with mutations in genes encoding epidermal structural proteins, barrier enzymes, and their inhibitors; the role of genes regulating innate and adaptive immune responses and environmental factors inducing the disease is also noted. Recent studies point to the key role of epigenetic changes in the development of the disease. Epigenetic modifications...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublikacjaBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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Genetic and biochemical characterization of yeasts isolated from Antarctic soil samples
PublikacjaThe Polish Arctowski Station is situated in the maritime Antarctic on the western shore ot' Admiralty Bay and encompasses terrestrial habitats which are not perma-nently covered by ice, in contrast to morę than 90% of the island's surface area. Over the past several decades, stud-ies exploring the soils of those habitats have revealed a considerable diversity of bacteria, filamentous fungi, and, to a lesser extent, yeasts; however,...
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Real and Virtual Instruments in Machine Learning – Training and Comparison of Classification Results
PublikacjaThe continuous growth of the computing power of processors, as well as the fact that computational clusters can be created from combined machines, allows for increasing the complexity of algorithms that can be trained. The process, however, requires expanding the basis of the training sets. One of the main obstacles in music classification is the lack of high-quality, real-life recording database for every instrument with a variety...
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Moving object tracking algorithm evaluation in autonomous surveillance system
PublikacjaResults of evaluation of video object tracking algorithm being a part of an autonomous surveillance system are presented. The algorithm was investigated employing a set of benchmarks recorded locally. The precision of object detection, evaluated with such metrics as fragmentation, object area recall and object precision, is in focus. The experiments aimed at examining the detection quality using various object detection algorithm...
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Processes of enhancing the intelligence of Learning Organizations on the basis of Competence Centers
PublikacjaThe process of organizational learning and proper knowledge management became today one of the major challenges for the organization acting in the knowledge-based economy. According to the observations of the authors of this paper the demand for formalization of knowledge management processes and organizational learning is particularly evident in research institutions, established either by the universities, or the companies. The...
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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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Low-Cost Quasi-Global Optimization of Expensive Electromagnetic Simulation Models by Inverse Surrogates and Response Features
PublikacjaConceptual design of contemporary high-frequency structures is typically followed by a careful tuning of their parameters, predominantly the geometry ones. The process aims at improving the relevant performance figures, and may be quite expensive. The reason is that conventional design methods, e.g., based on analytical or equivalent network models, often only yield rough initial designs. This is especially the case for miniaturized...
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Zastosowanie algorytmu ewolucyjnego do uczenia neuronowego regulatora napięcia generatora synchronicznego. Evolutionary algorithm for training a neural network of synchronous generator voltage controller
PublikacjaNajpopularniejsza metoda uczenia wielowarstwowych sieci neuronowych -metoda wstecznej propagacji błędu - charakteryzuje się słabą efektywnością. Z tego względu podejmowane są próby stosowania innych metod do uczenia sieci. W pracy przedstawiono wyniki uczenia sieci realizującej regulator neuronowy, za pomocą algorytmu ewolucyjnego. Obliczenia symulacyjne potwierdziły dobrą zbieżność algorytmu ewolucyjnego w tym zastosowaniu.
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Numerically Efficient Miniaturization-Oriented Optimization of an Ultra-Wideband Spline-Parameterized Antenna
PublikacjaDesign of ultra-wideband radiators for modern handheld applications is a challenging task that involves not only selection of an appropriate topology, but also its tuning oriented towards balancing the electrical performance and size. In this work, a low-cost design of a compact, broadband, spline-parameterized monopole antenna has been considered. The framework used for the structure design implements trust-region-based methods,...
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Automatic Singing Voice Recognition EmployingNeural Networks and Rough Sets
PublikacjaCelem badań jest automatyczne rozpoznawanie głosów śpiewaczych w kategorii rodzaju i jakości technicznej śpiewu. W artykule opisano stworzoną bazę danych głosów, która zawiera próbki głosu śpiewaków profesjonalnych i amatorskich. W dalszej części opisano parametry zdefiniowane w oparciu o zjawiska biomechaniczne w narządzie głosu podczas śpiewania. W oparciu o stworzone macierze parametrów wytrenowano i porównano automatyczne klasyfikatory...
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Impact of the Artificial Strait in the Vistula Spit on the Hydrodynamics of the Vistula Lagoon (Baltic Sea)
PublikacjaIn the Vistula Lagoon, storm surges are induced by variable sea levels in the Gulf of Gdańsk and wind action. The rising of the water level in the southern part of the basin, exceeding 1.0 m above mean sea level, can be dangerous for the lowland area of Żuławy Elbląskie, causing the inundation of the polders adjacent to the lagoon. One of the potential possibilities to limit the flood risk is to decrease the water level in the...
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Hardware implementation of digital image stabilization using optical flow algorithm and FPGA technology
PublikacjaW artykule przedstawiono efektywną procedurę uproszczenia algorytmu przepływu optycznego oraz jego realizację w układzie programowalnym FPGA. Zmodyfikowany algorytm wykorzystuję metodę blokowego dopasowania podobszarów oraz jednowymiarową reprezentację podobszarów. Dodatkowo, funkcja korelacji oparta jest o normę L1. W rezultacie uzyskano zmniejszenie zużytych zasobów kosztem nieznacznej utraty dokładności. Zarówno dokładność,...
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The Cultures of Knowledge Organizations: Knowledge, Learning, Collaboration (KLC)
PublikacjaThis book focuses on seeing, understanding, and learning to shape an organization’s essential cultures. The book is grounded on a fundamental assumption that every organization has a de facto culture. These “de facto cultures” appear at first glance to be serendipitous, vague, invisible, and unmanaged. An invisible and unrecognized de facto culture can undermine business goals and strategies and lead to business failures. The authors...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublikacjaSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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Pose-Invariant Face Detection by Replacing Deep Neurons with Capsules for Thermal Imagery in Telemedicine
PublikacjaAbstract— The aim of this work was to examine the potential of thermal imaging as a cost-effective tool for convenient, non- intrusive remote monitoring of elderly people in different possible head orientations, without imposing specific behavior on users, e.g. looking toward the camera. Illumination and pose invariant head tracking is important for many medical applications as it can provide information, e.g. about vital signs, sensory...
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Activation maps of convolutional neural networks as a tool for brain degeneration tracking in early diagnosis of dementia in Parkinson's disease based on magnetic resonance imaging
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Model Predictive Controller for Integrated Wastewater Treatment System
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Predictive current controller for sensorless induction motor drive
PublikacjaPrzedstawiono układ bezczujnikowego sterowania dla napedu z silnikiem klatkowym przy zastosowaniu predykcyjnego regulatora pradu. Zastosowany obserwator adaptacyjny wykazuje dużą odporność na zmiany parametrów silnika. W obserwatorze obliczane są wartości sił elektromotorycznych wykorzystywane w procesie regulacji predykcyjnej pradu silnika. Pokazano wyniki badań symulacyjnych i eksperymentalnych.
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Predictive control system of the shunt active power filter
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Model predictive controller for integrated wastewater treatment systems.
PublikacjaSterowanie optymalizujace systemem oczyszczania ścieków (WWTS) pozwala na zmniejszenie kosztów operacyjnych przy jednoczesnym spełnieniu narzuconych ograniczeń na wypływające ścieki, jednak wymaga zaawansowanych technologii sterowania. Sterowanie predykcyjne z modelem (MPC) jest bardzo użyteczną technologią sterowania takimi systemami. MPC doskonale radzi sobie z obecnością ogrniczeń na wielkości wyjściowe, wielowymiarowością problemu...
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Novel “acid tuned” deep eutectic solvents based on protonated L-proline
PublikacjaThe paper presents new types of deep eutectic solvents (DESs) based on L-proline protonated using three different acids (hydrochloric, sulfuric and phosphoric)and playing the role of a hydrogen bond acceptor(HBA). Glucose and xylitol were used as hydrogen bond donors (HBD). A series of deep eutectic solvents with various mole ratios were obtained for the systems L-proline: glucose and L-proline: xylitol. Density, melting point,...
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Deep eutectic solvents vs ionic liquids: Similarities and differences
PublikacjaDeep eutectic solvents (DES) were introduced as an alternative to ionic liquids (IL) to overcome the drawbacks of IL solvents. However, some authors consider them to be a subclass of ILs. In contrast, other authors emphasize that these are by their nature independent, different groups of substances. Thus, the question arises: Which solvent group should DESs belong to? Maybe a new class should be added to the existing ones. The...
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Using River Formation Dynamics Algorithm in Mobile Robot Navigation
PublikacjaRiver Formation Dynamics is a heuristic optimization algorithm based on the manner, in which drops of water form the river bed. The idea is to imitate the movement of drops on the edges between given nodes thus performing a search based on their height, which is modified through the mechanism of soil erosion and sediment deposition. In this way decreasing gradients are constructed, and these are followed by subsequent drops to...
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Deep eutectic solvents with solid supports used in microextraction processes applied for endocrine-disrupting chemicals
PublikacjaThe determination of endocrine-disrupting chemicals (EDCs) has become one of the biggest challenges in Analytical Chemistry. Due to the low concentration of these compounds in different kinds of samples, it becomes necessary to employ efficient sample preparation methods and sensitive measurement techniques to achieve low limits of detection. This issue becomes even more struggling when the principles of the Green Analytical Chemistry...
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Mobility Managment Scenarios for IPv6 Networks-Proxy Mobile IP-v6Implementation Issues
PublikacjaManagement of user at the network layer plays an important role in efficient network operation. In the paper, authors' implementation of one of network-based mobility management models, namely Proxy Mobile IPv6, is presented and tested in a number of networking topologies and communication scenarios. The proposed implementation covers PMPIv6 functionality with optional security extensions (use of Diameter protocol) and handover...
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A METHOD OF TRUST MANAGEMENT IN WIRELESS SENSOR NETWORKS
PublikacjaThe research problem considered in this paper is how to protect wireless sensor networks (WSN) against cyber-threats by applying trust management and how to strengthen network resilience to attacks targeting the trust management mechanism itself. A new method, called WSN Cooperative Trust Management Method (WCT2M), of distributed trust management in multi-layer wireless sensor networks is proposed and its performance is evaluated....
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Complex Root Finding Algorithm Based on Delaunay Triangulation
PublikacjaA simple and flexible algorithm for finding zeros of a complex function is presented. An arbitrary-shaped search region can be considered and a very wide class of functions can be analyzed, including those containing singular points or even branch cuts. The proposed technique is based on sampling the function at nodes of a regular or a self-adaptive mesh and on the analysis of the function sign changes. As a result, a set of candidate points...
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Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis
PublikacjaWe proposed to apply a specific machine learning technique called Self-Organising Maps (SOM) to identify similarities in the performance of muscles around human temporomandibular joint (TMJ). The performance was assessed by measuring muscle activation with the use of surface electromyography (sEMG). SOM algorithm used in the study was able to find clusters of data in sEMG test results. The SOM analysis was based on processed sEMG...
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Identification of the Contamination Source Location in the Drinking Water Distribution System Based on the Neural Network Classifier
PublikacjaThe contamination ingression to the Water Distribution System (WDS) may have a major impact on the drinking water consumers health. In the case of the WDS contamination the data from the water quality sensors may be efficiently used for the appropriate disaster management. In this paper the methodology based on the Learning Vector Quantization (LVQ) neural network classifier for the identification of the contamination source location...
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Noise profiling for speech enhancement employing machine learning models
PublikacjaThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...