Search results for: INTELLIGENT SIGNAL PROCESSING, MACHINE LEARNING, DATASETS
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Federated Learning in Healthcare Industry: Mammography Case Study
PublicationThe paper focuses on the role of federated learning in a healthcare environment. The experimental setup involved different healthcare providers, each with their datasets. A comparison was made between training a deep learning model using traditional methods, where all the data is stored in one place, and using federated learning, where the data is distributed among the workers. The experiment aimed to identify possible challenges...
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A Concept of Automatic Film Color Grading Based on Music Recognition and Evoked Emotions
PublicationThe article presents the aspects of the final selection of the color of shots in film production based on the psychology of color. First of all, the elements of color processing, contrast, saturation or white balance in the film shots were presented and the definition of color grading was given. In the second part of the article the analysis of film music was conducted in the context of stimulating appropriate emotions while watching...
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Adaptive Hounsfield Scale Windowing in Computed Tomography Liver Segmentation
PublicationIn computed tomography (CT) imaging, the Hounsfield Unit (HU) scale quantifies radiodensity, but its nonlinear nature across organs and lesions complicates machine learning analysis. This paper introduces an automated method for adaptive HU scale windowing in deep learning-based CT liver segmentation. We propose a new neural network layer that optimizes HU scale window parameters during training. Experiments on the Liver Tumor...
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Experience-Based Cognition for Driving Behavioral Fingerprint Extraction
PublicationABSTRACT With the rapid progress of information technologies, cars have been made increasingly intelligent. This allows cars to act as cognitive agents, i.e., to acquire knowledge and understanding of the driving habits and behavioral characteristics of drivers (i.e., driving behavioral fingerprint) through experience. Such knowledge can be then reused to facilitate the interaction between a car and its driver, and to develop better and...
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Olgun Aydin Dr
PeopleOlgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Senior Data Scientist in PwC Poland, gives lectures in Gdansk University of Technology in Poland and member of WhyR? Foundation. Olgun is a very big fan of R and author of the book called “R Web Scraping Quick Start Guide” , two video courses are called “Deep Dive into Statistical Modelling using R” and “Applied Machine Learning and Deep...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_004)
Open Research DataData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_005)
Open Research DataData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_0010)
Open Research DataData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_002)
Open Research DataData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_0012)
Open Research DataData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_008)
Open Research DataData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_003)
Open Research DataData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_007)
Open Research DataData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_006)
Open Research DataData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_0011)
Open Research DataData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_009)
Open Research DataData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_0017)
Open Research DataData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_0021)
Open Research DataData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_0020)
Open Research DataData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_0019)
Open Research DataData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_0024)
Open Research DataData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_0023)
Open Research DataData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Implementation of DIFAR Processing in ASW Dipping Sonar
PublicationThis paper presents the implementation of the signal processing algorithm used by buoy DIFAR (Directional Frequency Analysis and Recording), that is fully operational on Polish Navy anti-submarine warfare (ASW) helicopters and ships, applied to dipping sonars for detection and tracking of submarines. The development of the DSP algorithms was a part of the modernization of sonars conducted at the Gdansk University of Technology....
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Voltage fluctuations on the main switchgear of the industrial power system supplying the rolling mill motors
Open Research DataThe dataset presents the voltage waveforms on the bus bars of the main switchgear of the industrial power network for the supply of rolling mills. The data was recorded during an experiment whose purpose was to determine a level of short-term and long-term flicker caused by voltage fluctuations. In the virtual application of flickermeter, a hardware...
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International Conference in Methodologies and Intelligent Systems for Technology Enhanced Learning
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Adaptive system for recognition of sounds indicating threats to security of people and property employing parallel processing of audio data streams
PublicationA system for recognition of threatening acoustic events employing parallel processing on a supercomputing cluster is featured. The methods for detection, parameterization and classication of acoustic events are introduced. The recognition engine is based onthreshold-based detection with adaptive threshold and Support Vector Machine classifcation. Spectral, temporal and mel-frequency descriptors are used as signal features. The...
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RENOVATION OF ARCHIVE AUDIO RECORDINGS USING SPARSE AUTOREGRESSIVE MODELING AND BIDIRECTIONAL PROCESSING
PublicationThe paper presents a new approach to elimination of broadband noise and impulsive disturbances from archive audio recordings. The proposed adaptive Kalman-like algorithm, based on a sparse autoregressive model of the audio signal, simultaneously detects noise pulses, interpolates the irrevocably distorted samples and performs signal smoothing. It is shown that bidirectional (forward-backward) processing of the archive signal improves...
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A Robust Random Forest Model for Classifying the Severity of Partial Discharges in Dielectrics
PublicationPartial Discharges (PDs) are a common source of degradation in electrical assets. It is essential that the extent of the deterioration level of insulating medium is correctly identified, to optimize maintenance schedules and prevent abrupt power outages. Temporal PD signals received from damaged insulation, collected through the IEC-60270 method is the gold standard for PD detection. Temporal signals may be transformed to the frequency...
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Basic evaluation of limb exercises based on electromyography and classification methods
PublicationSymptoms caused by cerebral palsy or stroke deprive a person partially or even completely of his ability to move. Nowadays we can observe more technologically advanced rehabilitation devices which incorporate biofeedback into the process of rehabilitation of such people. However, there is still a lack of devices that would analyse, assess, and control (independently or with limited support) specialised movement exercises. Here...
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Joint workshop on Multimodal Interaction and Related Machine Learning Algorithms (now ICMI-MLMI)
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Uczenie maszynowe do samoorganizacji systemów rozproszonych w zastosowaniach gospodarczych
PublicationW pracy omówiono uczenie maszynowe do samoorganizacji systemów rozproszonych w zastosowaniach gospodarczych ze szczególnym uwzględnieniem sieci neuronowych do predykcji finansowych oraz szacowania ratingu przedsiębiorstw. Oprócz sieci neuronowych, istotną rolę w przygotowaniu i testowaniu informatycznych systemów finansowych może pełnić programowanie genetyczne. Z tego powodu omówiono uczenie maszynowe w aplikacjach konstruowanych...
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Load effect impact on the exploitation of concrete machine foundations used in the gas and oil industry
PublicationMachine foundations is a critical topic in the gas and oil industry, which design and exploitation require extensive technical knowledge. Machine foundations are the constructions which are intended for mounting on it a specific type of machine. The foundation has to transfer dynamic and static load from machine to the ground. The primary difference between machine foundations and building foundations is that the machine foundations...
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Investigating Feature Spaces for Isolated Word Recognition
PublicationThe study addresses the issues related to the appropriateness of a two-dimensional representation of speech signal for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and time-frequency signal representation converted to the investigated feature spaces. In particular, waveforms and fractal dimension features of the signal were chosen for the time domain, and...
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Detecting Lombard Speech Using Deep Learning Approach
PublicationRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublicationTo successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...
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The effect of current signal filtering method on the value of cutting power while sawing wood
PublicationThe goal of this work was to investigate an effect of various signal pre-processings on the outline of the electrical power curve and its influence on the measured cutting force estimation. Two signal processing methods were selected for the needs of the experiment, including digital filter and wavelet transform. The filter used was Butterworth, 3rd order band-stop with the cut-out band from 45 Hz to 55 Hz. The second approach...
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Review of the Complexity of Managing Big Data of the Internet of Things
PublicationTere is a growing awareness that the complexity of managing Big Data is one of the main challenges in the developing feld of the Internet of Tings (IoT). Complexity arises from several aspects of the Big Data life cycle, such as gathering data, storing them onto cloud servers, cleaning and integrating the data, a process involving the last advances in ontologies, such as Extensible Markup Language (XML) and Resource Description...
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Multiplicative Long Short-Term Memory with Improved Mayfly Optimization for LULC Classification
PublicationLand 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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Harmony Search to Self-Configuration of Fault-Tolerant Grids for Big Data
PublicationIn this paper, harmony search algorithms have been proposed to self-configuration of fault-tolerant grids for big data processing. Some tasks related to big data processing have been considered. Moreover, two criteria have been applied to evaluate quality of grids. The first criterion is a probability that all tasks meet their deadlines and the second one is grid reliability. Furthermore, some intelligent agents based on harmony...
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International Conference on Intelligent Text Processing and Computational Linguistics
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IEEE International Conference on Intelligent Computer Communication and Processing
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Data Acquisition and Processing for GeoAI Models to Support Sustainable Agricultural Practices
PublicationThere are growing opportunities to leverage new technologies and data sources to address global problems related to sustainability, climate change, and biodiversity loss. The emerging discipline of GeoAI resulting from the convergence of AI and Geospatial science (Geo-AI) is enabling the possibility to harness the increasingly available open Earth Observation data collected from different constellations of satellites and sensors...
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Client-side versus server-side geographic data processing performance comparison: Data and code
PublicationThe data and code presented in this article are related to the research article entitled “Analysis of Server-side and Client-side Web-GIS data processing methods on the example of JTS and JSTS using open data from OSM and Geoportal” (Kulawiak et al., 2019). The provided 12 datasets include multi-point and multi-polygon data of different scales and volumes, representing real-world geographic features. The datasets cover the area...
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Comparative study on the effectiveness of various types of road traffic intensity detectors
PublicationVehicle detection and speed measurements are crucial tasks in traffic monitoring systems. In this work, we focus on several types of electronic sensors, operating on different physical principles in order to compare their effectiveness in real traffic conditions. Commercial solutions are based on road tubes, microwave sensors, LiDARs, and video cameras. Distributed traffic monitoring systems require a high number of monitoring...
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Real-time speech-rate modification experiments
PublicationAn algorithm designed for real-time speech time scale modification (stretching) is proposed, providing a combination of typical synchronous overlap and add based time scale modification algorithm and signal redundancy detection algorithms that allow to remove parts of the speech signal and replace them with the stretched speech signal fragments. Effectiveness of signal processing algorithms are examined experimentally together...
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Methods for quality improvement of multibeam and LiDAR point cloud data in the context of 3D surface reconstruction
PublicationPoint cloud dataset is the transitional data model used in several marine and land remote-sensing applications. During further steps of processing, the transformation of point cloud spatial data to more complex models containing higher order geometric structures like edges and facets may be possible, if an appropriate quality level of input data is provided. Point cloud datasets usually contain a considerable amount of undesirable...
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Integration, Processing and Dissemination of LiDAR Data in a 3D Web-GIS
PublicationThe rapid increase in applications of Light Detection and Ranging (LiDAR) scanners, followed by the development of various methods that are dedicated for survey data processing, visualization, and dissemination constituted the need of new open standards for storage and online distribution of collected three-dimensional data. However, over a decade of research in the area has resulted in a number of incompatible solutions that offer...
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Building collective intelligence through experience: a survey on the use of the KREM model
PublicationThis article presents a survey on the use of KREM, a generic knowledge-based framework for building collective intelligence through experience. After a discussion on the disadvantages of the traditional architecture used to deploy intelligent systems, the KREM architecture (Knowledge, Rules, Experience, Meta-Knowledge) is presented. The novelty of the proposal comes from the inclusion of the capitalisation of experience and the...
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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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General concept of reduction process for big data obtained by interferometric methods
PublicationInterferometric sonar systems apply the phase content of the sonar signal to measure the angle of a wave front returned from the seafloor or from a target. It collect a big data – datasets that are so large or complex that traditional data processing application software is inadequate to deal with them. The recording a large number of data is associated with the difficulty of their efficient use. So data have to be reduced. The main...