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Wyniki wyszukiwania dla: CLASSIFICATION OF T-EQUIVARIANT MAPS
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Chlorinated solvents in a petrochemical wastewater treatment plant: Anassessment of their removal using self-organising maps
PublikacjaThe self-organising map approach was used to assess the efficiency of chlorinated solvent removal frompetrochemical wastewater in a refinery wastewater treatment plant. Chlorinated solvents and inorganicanions (11 variables) were determined in 72 wastewater samples, collected from three different purificationstreams. The classification of variables identified technical solvents, brine from oil desalting andrunoff sulphates as pollution...
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Development of an AI-based audiogram classification method for patient referral
PublikacjaHearing loss is one of the most significant sensory disabilities. It can have various negative effects on a person's quality of life, ranging from impeded school and academic performance to total social isolation in severe cases. It is therefore vital that early symptoms of hearing loss are diagnosed quickly and accurately. Audiology tests are commonly performed with the use of tonal audiometry, which measures a patient's hearing...
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Improving the Accuracy in Sentiment Classification in the Light of Modelling the Latent Semantic Relations
PublikacjaThe research presents the methodology of improving the accuracy in sentiment classification in the light of modelling the latent semantic relations (LSR). The objective of this methodology is to find ways of eliminating the limitations of the discriminant and probabilistic methods for LSR revealing and customizing the sentiment classification process (SCP) to the more accurate recognition of text tonality. This objective was achieved...
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Classification of objects in the LIDAR point clouds using Deep Neural Networks based on the PointNet model
PublikacjaThis work attempts to meet the challenges associated with the classification of LIDAR point clouds by means of deep learning. In addition to achieving high accuracy, the designed system should allow the classification of point clouds covering an area of several dozen square kilometers within a reasonable time interval. Therefore, it must be characterized by fast processing and efficient use of memory. Thus, the most popular approaches...
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Comparison of Methods for Real and Imaginary Motion Classification from EEG Signals
PublikacjaA method for feature extraction and results of classification of EEG signals obtained from performed and imagined motion are presented. A set of 615 features was obtained to serve for the recognition of type and laterality of motion using 8 different classifications approaches. A comparison of achieved classifiers accuracy is presented in the paper, and then conclusions and discussion are provided. Among applied algorithms the...
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An Overview of the Development of a Real-Time System for Endoscopic Video Classification
PublikacjaThe article presents the results of improving endoscopic image classification algorithms in an effort towards applying them in a real-time diagnosis supporting system. Methods for the detection and removal of personal data are presented and discussed. The currently developed recognition algorithms have been improved in terms of accuracy and performance to make them suitable for a real-life implementation. Their test results are...
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Traffic Noise Analysis Applied to Automatic Vehicle Counting and Classification
PublikacjaProblems related to determining traffic noise characteristics are discussed in the context of automatic dynamic noise analysis based on noise level measurements and traffic prediction models. The obtained analytical results provide the second goal of the study, namely automatic vehicle counting and classification. Several traffic prediction models are presented and compared to the results of in-situ noise level measurements. Synchronized...
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Efficiency of Artificial Intelligence Methods for Hearing Loss Type Classification: an Evaluation
PublikacjaThe evaluation of hearing loss is primarily conducted by pure tone audiometry testing, which is often regarded as golden standard for assessing auditory function. If the presence of hearing loss is determined, it is possible to differentiate between three types of hearing loss: sensorineural, conductive, and mixed. This study presents a comprehensive comparison of a variety of AI classification models, performed on 4007 pure tone...
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Bimodal deep learning model for subjectively enhanced emotion classification in films
PublikacjaThis research delves into the concept of color grading in film, focusing on how color influences the emotional response of the audience. The study commenced by recalling state-of-the-art works that process audio-video signals and associated emotions by machine learning. Then, assumptions of subjective tests for refining and validating an emotion model for assigning specific emotional labels to selected film excerpts were presented....
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Computed aided system for separation and classification of the abnormal erythrocytes in human blood
PublikacjaThe human peripheral blood consists of cells (red cells, white cells, and platelets) suspended in plasma. In the following research the team assessed an influence of nanodiamond particles on blood elements over various periods of time. The material used in the study consisted of samples taken from ten healthy humans of various age, different blood types and both sexes. The markings were leaded by adding to the blood unmodified...
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Justyna Signerska-Rynkowska dr inż.
OsobySince 2021 visiting assistant professor in Dioscuri Centre in Topological Data Analysis (Institute of Mathematics of the Polish Academy of Sciences, IMPAN) Since 2016 assistant professor at Gdańsk University of Technology, Faculty of Applied Physics and Mathematics, Department of Differential Equations and Mathematics Applications 2020 - 2023 Principal Investigator in "SONATA" grant “Challenges of low-dimensional...
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Classification of submandibular salivary stones based on ultrastructural studies
PublikacjaIntroduction: Sialolithiasis remains a clinical problem with unclear etiopathogenesis, lack of prevention methods, and only surgical treatment. Materials and methods: An ultrastructure examination of submandibular sialoliths obtained from patients with chronic sialolithiasis was conducted using a scanning electron microscope and X‐ray photoelectron spectroscopy. Results: Based on the results, we divided sialoliths into three types:...
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Algebraic periods and minimal number of periodic points for smooth self-maps of 1-connected 4-manifolds with definite intersection forms
PublikacjaLet M be a closed 1-connected smooth 4-manifolds, and let r be a non-negative integer. We study the problem of finding minimal number of r-periodic points in the smooth homotopy class of a given map f: M-->M. This task is related to determining a topological invariant D^4_r[f], defined in Graff and Jezierski (Forum Math 21(3):491–509, 2009), expressed in terms of Lefschetz numbers of iterations and local fixed point indices of...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublikacjaThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Classification of submandibular salivary stones based on ultrastructural studies
PublikacjaIntroduction: Sialolithiasis remains a clinical problem with unclear etiopathogenesis, lack of prevention methods, and only surgical treatment. Materials and methods: An ultrastructure examination of submandibular sialoliths obtained from patients with chronic sialolithiasis was conducted using a scanning electron microscope and X-ray photoelectron...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublikacjaSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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Influence of accelerometer signal pre-processing and classification method on human activity recognition
PublikacjaA study of data pre-processing influence on accelerometer-based human activity recognition algorithms is presented. The frequency band used to filter-out the accelerometer signals and the number of accelerometers involved were considered in terms of their influence on the recognition accuracy. In the test four methods of classification were used: support vector machine, decision trees, neural network, k-nearest neighbor.
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INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublikacjaIn recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...
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On the Role of Polarimetric Decomposition and Speckle Filtering Methods for C-Band SAR Wetland Classification Purposes
PublikacjaPrevious wetlands studies have thoroughly verified the usefulness of data from synthetic aperture radar (SAR) sensors in various acquisition modes. However, the effect of the processing parameters in wetland classification remains poorly explored. In this study, we investigated the influence of speckle filters and decomposition methods with different combinations of filter and decomposition windows sizes on classification accuracy....
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Spatio-Temporal Validation of GNSS-Derived Global Ionosphere Maps Using 16 Years of Jason Satellites Observations
PublikacjaExisting ionospheric models perform very well in mapping the calm state of the ionosphere. However, the problem is accurately determining the total electron content (TEC) for disturbed days. Knowledge of the exact electron density is essential for single−frequency receivers, which cannot eliminate the ionospheric delay. This study aims to investigate temporal and spatial variability in the distribution of TEC based on differences...
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Pose classification in the gesture recognition using the linear optical sensor
PublikacjaGesture sensors for mobile devices, which have a capability of distinguishing hand poses, require efficient and accurate classifiers in order to recognize gestures based on the sequences of primitives. Two methods of poses recognition for the optical linear sensor were proposed and validated. The Gaussian distribution fitting and Artificial Neural Network based methods represent two kinds of classification approaches. Three types...
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Novel approach to ecotoxicological risk assessment of sediments cores around the shipwreck by the use of self-organizing maps
PublikacjaMarine and coastal pollution plays an increasingly important role due to recent severe accidents which drew attention to the consequences of oil spills causing widespread devastation of marine ecosystems. All these problems cannot be solved without conducting environmental studies in the area of possible oil spill and performing chemometric evaluation of the data obtained looking for similar patterns among pollutants and optimize...
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A Framework for Adaptive and Integrated Classification
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Piroxicam derivatives THz classification
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Classification Research On Intraoperative Neuromonitoring
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Chemometrics for Selection, Prediction, and Classification of Sustainable Solutions for Green Chemistry—A Review
PublikacjaIn this review, we present the applications of chemometric techniques for green and sustainable chemistry. The techniques, such as cluster analysis, principal component analysis, artificial neural networks, and multivariate ranking techniques, are applied for dealing with missing data, grouping or classification purposes, selection of green material, or processes. The areas of application are mainly finding sustainable solutions...
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SYNAT_MUSIC_GENRE_FV_173
Dane BadawczeThis is the original dataset containing 51582 music tracks (22 music genres) and 173 element-feature vector [1-6,9]. A collection of more than 50000 music excerpts described with a set of descriptors obtained through the analysis of 30-second mp3 recordings was gathered in a database called SYNAT. The SYNAT database was realized by the Gdansk University...
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Displacement piles - classification and methods for the calculation of bearing capacity.
PublikacjaDisplacement piles belong to a group of technologies whose main idea is to install or make a pile without extracting ground material. According to definition, contained in PN-EN:1997-1:2008, displacement piles should be considered as driven, pressed in using vibrators and made with the use of spread augers. The classification of piles used so far with regard to the technology of execution is modified. An additional element is the...
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Automatic classification and mapping of the seabed using airborne LiDAR bathymetry
PublikacjaShallow coastal areas are among the most inhabited areas and are valuable for biodiversity, recreation and the economy. Due to climate change and sea level rise, sustainable management of coastal areas involves extensive exploration, monitoring, and protection. Current high-resolution remote sensing methods for monitoring these areas include bathymetric LiDAR. Therefore, this study presents a novel methodological approach to assess...
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Local fixed point indices of iterations of planar maps
PublikacjaW artykule podana zostaje postać indeksów iteracji dla pewnej klasy odwzorowań planarnych. Podstawowymi narzędziami stosowanym w pracy są liczba Nielsena i indeks Conleya.
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Periodic points of latitudinal maps of the $m$-dimensional sphere
PublikacjaLet f be a smooth self-map of the m-dimensional sphere Sm. Under the assumption that f preserves latitudinal foliations with the fibres S1, we estimate from below the number of fixed points of the iterates of f. The paper generalizes the results obtained by Pugh and Shub and by Misiurewicz.
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Automated hearing loss type classification based on pure tone audiometry data
PublikacjaHearing problems are commonly diagnosed with the use of tonal audiometry, which measures a patient’s hearing threshold in both air and bone conduction at various frequencies. Results of audiometry tests, usually represented graphically in the form of an audiogram, need to be interpreted by a professional audiologist in order to determine the exact type of hearing loss and administer proper treatment. However, the small number of...
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublikacjaThe paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...
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Music genre classification applied to bass enhancement for mobile technology
PublikacjaThe aim of this paper is to present a novel approach to the Virtual Bass Synthesis (VBS) algorithms applied to portable computers. The proposed algorithm is related to intelligent, rule-based setting of synthesis parameters according to music genre of an audio excerpt. The classification of music genres is automatically executed employing MPEG 7 parameters and the Principal Component Analysis method applied to reduce information...
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Comparative Study of Self-Organizing Maps vs. Subjective Evaluation of Quality of Allophone Pronunciation for Nonnative English Speakers
PublikacjaThe purpose of this study was to apply Self-Organizing Maps to differentiate between the correct and the incorrect allophone pronunciations and to compare the results with subjective evaluation. Recordings of a list of target words, containing selected allophones of English plosive consonants, the velar nasal and the lateral consonant, were made twice. First, the target words were read from the list by 9 non-native speakers and...
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublikacjaThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
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Brief Literature Review and Classification System of Reliability Methods for Evaluating the Stability of Earth Slopes
PublikacjaThe issue of slope stability is one of the most important and yet most difficult geotechnical problems. Assessing slope stability is particularly difficult because of the many uncertainties involved in the process. To take these uncertainties into account, probabilistic methods are used, and the reliability approach is adopted. There are many methods for reliability assessment of earth slope stability. However, there is no system...
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A Study on Influence of Normalization Methods on Music Genre Classification Results Employing kNN Algorithms
PublikacjaThis paper presents a comparison of different normalization methods applied to the set of feature vectors of music pieces. Test results show the influence of min-nlax and Zero-Mean normalization methods, employing different distance functions (Euclidean, Manhattan, Chebyshev, Minkowski) as a pre-processing for genre classification, on k-Nearest Neighbor (kNN) algorithm classification results.
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Developing assumptions for the tram noise attenuation passive system using the noise maps analysis method
PublikacjaThe paper presents experimental research carried out to determine the possible actions to reduce thenoise generated by trams in a highly urbanised area. A few design strategies affecting tram ride qualityhave been presented – especially in the aspect of the acoustic phenomena. Main sources of the noisein trams were characterised. The paper includes selected results of comprehensive...
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Classification of Landscape Physiognomies in Rural Poland: The Case of the Municipality of Cekcyn
PublikacjaThis article presents a methodology and the results of the classification of the rural landscapes physiognomies conducted on the study area located in the municipality of Cekcyn, Poland. The study aimed to develop a landscape identification method that would combine natural, cultural, and visual criteria with which to implement the provisions of the European Landscape Convention. The realization of the European Landscape Convention...
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ReFlexeNN - the Wearable EMG Interface with Neural Network Based Gesture Classification
PublikacjaThe electromyographic activity of muscles was measured using a wireless biofeedback device. The aim of the study was to examine the possibility of creating an automatic muscle tension classifier. Several measurement series were conducted and the participant performed simple physical exercises - forcing the muscle to increase its activity accordingly to the selected scale. A small wireless device was attached to the electrodes placed...
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Food Classification from Images Using a Neural Network Based Approach with NVIDIA Volta and Pascal GPUs
PublikacjaIn the paper we investigate the problem of food classification from images, for the Food-101 dataset extended with 31 additional food classes from Polish cuisine. We adopted transfer learning and firstly measured training times for models such as MobileNet, MobileNetV2, ResNet50, ResNet50V2, ResNet101, ResNet101V2, InceptionV3, InceptionResNetV2, Xception, NasNetMobile and DenseNet, for systems with NVIDIA Tesla V100 (Volta) and...
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Selection of an artificial pre-training neural network for the classification of inland vessels based on their images
PublikacjaArtificial neural networks (ANN) are the most commonly used algorithms for image classification problems. An image classifier takes an image or video as input and classifies it into one of the possible categories that it was trained to identify. They are applied in various areas such as security, defense, healthcare, biology, forensics, communication, etc. There is no need to create one’s own ANN because there are several pre-trained...
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Detection, classification and localization of acoustic events in the presence of background noise for acoustic surveillance of hazardous situations
PublikacjaEvaluation of sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for discerning between the events being in focus and the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the...
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Smart Virtual Bass Synthesis Algorithm Based on Music Genre Classification
PublikacjaThe aim of this paper is to present a novel approach to the Virtual Bass Synthesis (VBS) algorithms applied to portable computers. The proposed algorithm employed automatic music genre recognition to determine the optimum parameters for the synthesis of additional frequencies. The synthesis was carried out using the non-linear device (NLD) and phase vocoder (PV) methods depending on the music excerpt genre. Classification of musical...
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Multiplicative Long Short-Term Memory with Improved Mayfly Optimization for LULC Classification
PublikacjaLand Use and Land Cover (LULC) monitoring is crucial for global transformation, sustainable land control, urban planning, urban growth prediction, and the establishment of climate regulations for long-term development. Remote sensing images have become increasingly important in many environmental planning and land use surveys in recent times. LULC is evaluated in this research using the Sat 4, Sat 6, and Eurosat datasets. Various...
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Evaluation of sound event detection, classification and localization in the presence of background noise for acoustic surveillance of hazardous situations
PublikacjaAn evaluation of the sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for separating foreground events from the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the classifier...
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Dynamics of Systems with a Discontinuous Hysteresis Operator and Interval Translation Maps
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Petrographic, mineralogical, and climatic analyses, and risk maps for conservation strategies
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Indices of interations and periodic points of simplical maps of smooth type
PublikacjaW pracy dowodzi się symplicjalnego odpowiednika twierdzenia Chowa, Mallet-Paret i Yorke´a. Otrzymany wynik służy do badania punktów periodycznych odwzorowań symplicjalnych gładkiego typu.