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Wyniki wyszukiwania dla: UNSUPERVISED LEARNING
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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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Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublikacjaIdentification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to classify active electrodes showing event-related intracranial EEG (iEEG) responses from 115 patients performing a free recall verbal memory task. Our approach employed new interpretable...
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Revisiting Supervision for Continual Representation Learning
Publikacja"In the field of continual learning, models are designed to learn tasks one after the other. While most research has centered on supervised continual learning, there is a growing interest in unsupervised continual learning, which makes use of the vast amounts of unlabeled data. Recent studies have highlighted the strengths of unsupervised methods, particularly self-supervised learning, in providing robust representations. The improved...
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Categorization of Cloud Workload Types with Clustering
PublikacjaThe paper presents a new classification schema of IaaS cloud workloads types, based on the functional characteristics. We show the results of an experiment of automatic categorization performed with different benchmarks that represent particular workload types. Monitoring of resource utilization allowed us to construct workload models that can be processed with machine learning algorithms. The direct connection between the functional...
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Vident-synth: a synthetic intra-oral video dataset for optical flow estimation
Dane BadawczeWe introduce Vident-synth, a large dataset of synthetic dental videos with corresponding ground truth forward and backward optical flows and occlusion masks. It can be used for:
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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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Are Pair Trading Strategies Profitable During COVID-19 Period?
PublikacjaPair trading strategy is a well-known profitable strategy in stock, forex, and commodity markets. As most of the world stock markets declined during COVID-19 period, therefore this study is going to observe whether this strategy is still profitable after COVID-19 pandemic. One of the powerful algorithms of DBSCAN under the umbrella of unsupervised machine learning is applied and three clusters were formed by using market and accounting...
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Greencoin: prototype of a mobile application facilitating and evidencing pro-environmental behavior of citizens
PublikacjaAmong many global challenges, climate change is one of the biggest challenges of our times. While it is one of the most devastating problems humanity has ever faced, one question naturally arises: can individuals make a difference? We believe that everyone can contribute and make a difference to the community and lives of others. However, there is still a lack of effective strategies to promote and facilitate pro-environmental...
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Psychophysiological strategies for enhancing performance through imagery – skin conductance level analysis in guided vs. self-produced imagery
PublikacjaAthletes need to achieve their optimal level of arousal for peak performance. Visualization or mental rehearsal (i.e., Imagery) often helps to obtain an appropriate level of activation, which can be detected by monitoring Skin Conductance Level (SCL). However, different types of imagery could elicit different amount of physiological arousal. Therefore, this study aims: (1) to investigate differences in SCL associated with two instructional...
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Adaptacyjny system oświetlania dróg oraz inteligentnych miast
PublikacjaPrzedmiotem rozprawy jest zbadanie praktycznej możliwości wykrywania w czasie rzeczywistym anomalii w systemie oświetlenia drogowego w oparciu o analizę danych ze inteligentnych liczników energii. Zastosowanie inteligentnych liczników energii elektrycznej (Smart Meter) w systemach oświetlenia drogowego stwarza nowe możliwości w zakresie automatycznej diagnostyki takich niepożądanych zjawisk jak awarie lamp, odstępstwa od harmonogramu...
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Autoencoder application for anomaly detection in power consumption of lighting systems
PublikacjaDetecting energy consumption anomalies is a popular topic of industrial research, but there is a noticeable lack of research reported in the literature on energy consumption anomalies for road lighting systems. However, there is a need for such research because the lighting system, a key element of the Smart City concept, creates new monitoring opportunities and challenges. This paper examines algorithms based on the deep learning...
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Application of autoencoder to traffic noise analysis
PublikacjaThe aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...
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Vehicle detector training with minimal supervision
PublikacjaRecently many efficient object detectors based on convolutional neural networks (CNN) have been developed and they achieved impressive performance on many computer vision tasks. However, in order to achieve practical results, CNNs require really large annotated datasets for training. While many such databases are available, many of them can only be used for research purposes. Also some problems exist where such datasets are not...
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Robust unsupervised georeferencing algorithm for aerial and satellite imagery
PublikacjaIn order to eliminate a human factor and fully automate the process of embedding the spatial localization information in a remote sensed image the integrated georeferencing method was proposed. The paper presents this unsupervised and robust approach which is comprised of pattern recognition, using SIFT-based detector, and RANSAC based outlier removal with matching algorithm.
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Artificial intelligence models in prediction of response to cardiac resynchronization therapy: a systematic review
PublikacjaThe aim of the presented review is to summarize the literature data on the accuracy and clinical applicability of artificial intelligence (AI) models as a valuable alternative to the current guidelines in predicting cardiac resynchronization therapy (CRT) response and phenotyping of patients eligible for CRT implantation. This systematic review was performed...
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Induction of the common-sense hierarchies in lexical data
PublikacjaUnsupervised organization of a set of lexical concepts that captures common-sense knowledge inducting meaningful partitioning of data is described. Projection of data on principal components allow for dentification of clusters with wide margins, and the procedure is recursively repeated within each cluster. Application of this idea to a simple dataset describing animals created hierarchical partitioning with each clusters related...
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AI in the creation of the satellite maps
PublikacjaSatellite and aerial imagery acquisition is a very useful source of information for remote monitoring of the Earth’s surface. Modern satellite and aerial systems provide data about the details of the site topography, its characteristics due to different criteria (type of terrain, vegetation cover, soil type and moisture content), or even information about emergency situations or disasters. The paper proposes and discusses the process...
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LSA Is not Dead: Improving Results of Domain-Specific Information Retrieval System Using Stack Overflow Questions Tags
PublikacjaThe paper presents the approach to using tags from Stack Overflow questions as a data source in the process of building domain-specific unsupervised term embeddings. Using a huge dataset of Stack Overflow posts, our solution employs the LSA algorithm to learn latent representations of information technology terms. The paper also presents the Teamy.ai system, currently developed by Scalac company, which serves as a platform that...
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A nontargeted approach to determine the authenticity of Ginkgo biloba L. plant materials and dried leaf extracts by liquid chromatography-high-resolution mass spectrometry (LC-HRMS) and chemometrics
PublikacjaThe lack of stringent regulations regarding raw materials for herbal supplements used for medicinal purposes has been a constant challenge in the industry. Ginkgo biloba L. leaf extracts attract consumers because of the supposed positive effect on mental performance and memory. Supplements are produced using dried leaf materials and standardized leaf extracts such as EGb 761. Adulteration of Ginkgo biloba L. plants and extracts...
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Performance Comparison of Automatically Generated Topologically Agnostic Patch Antennas
PublikacjaReal-world antenna design typically relies on empirical methods, where the development starts with structure synthesis followed by its iterative adjustments to achieve the desired performance. Although the outlined approach proved to be successful, it is also dependent on engineering experience. Alternatively, development can be performed automatically based on the specifications. In this work, an unsupervised design of topologically...
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Vehicle Detection with Self-Training for Adaptative Video Processing Embedded Platform
PublikacjaTraffic monitoring from closed-circuit television (CCTV) cameras on embedded systems is the subject of the performed experiments. Solving this problem encounters difficulties related to the hardware limitations, and possible camera placement in various positions which affects the system performance. To satisfy the hardware requirements, vehicle detection is performed using a lightweight Convolutional Neural Network (CNN), named...
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Spectral Clustering Wikipedia Keyword-Based search Results
PublikacjaThe paper summarizes our research in the area of unsupervised categorization of Wikipedia articles. As a practical result of our research, we present an application of spectral clustering algorithm used for grouping Wikipedia search results. The main contribution of the paper is a representation method for Wikipedia articles that has been based on combination of words and links and used for categoriation of search results in this...
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Novel analytical method for detection of orange juice adulteration based on ultra-fast gas chromatography
PublikacjaThe food authenticity assessment is an increasingly important issue in food quality and safety. The application of an electronic nose based on ultra-fast gas chromatography technique enables rapid analysis of the volatile compounds from food samples. Due to the fact that this technique provides chemical profiling of natural products, it can be a powerful tool for authentication in combination with chemometrics. In this article,...
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Employing flowgraphs for forward route reconstruction in video surveillance system
PublikacjaPawlak’s flowgraphs were utilized as a base idea and knowledge container for prediction and decision making algorithms applied to experimental video surveillance system. The system is used for tracking people inside buildings in order to obtain information about their appearance and movement. The fields of view of the cameras did not overlap. Therefore, when an object was moving through unsupervised areas, prediction was needed...
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Floodsar: Automatic mapping of river flooding extent from multitemporal SAR imagery
PublikacjaFloodsar is an open-source tool for automatic mapping of the flood extent from a time series of synthetic aperture radar (SAR) imagery. Floodsar is unsupervised, however, it requires defining the parameters search space, geographical area of interest, and some river gauge observations (e.g. water levels or discharges) time series that overlap temporarily with the SAR imagery. Applications of Floodsar are mainly in real-time monitoring...
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On Unsupervised Artificial-Intelligence-Assisted Design of Antennas for High-Performance Planar Devices
PublikacjaDesign of modern antenna structures is a challenging endeavor. It is laborious, and heavily reliant on engineering insight and experience, especially at the initial stages oriented towards the devel-opment of a suitable antenna architecture. Due to its interactive nature and hands-on procedures (mainly parametric studies) for validating suitability of particular geometric setups, typical antenna development requires many weeks...
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Transcriptomic landscape of blood platelets in healthy donors
PublikacjaBACKGROUND Blood platelet RNA-sequencing is increasingly used among the scientific community. Aberrant platelet transcriptome is common in cancer or cardiovascular disease, but reference data on platelet RNA content in healthy individuals are scarce and merit complex investigation. METHODS We sought to explore the dynamics of platelet transcriptome. Datasets from 204 healthy donors were used for the analysis of splice variants,...
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Transcriptomic landscape of blood platelets in healthy donors
PublikacjaBlood platelet RNA-sequencing is increasingly used among the scientific community. Aberrant platelet transcriptome is common in cancer or cardiovascular disease, but reference data on platelet RNA content in healthy individuals are scarce and merit complex investigation. We sought to explore the dynamics of platelet transcriptome. Datasets from 204 healthy donors were used for the analysis of splice variants, particularly with...
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Assessment of Therapeutic Progress After Acquired Brain Injury Employing Electroencephalography and Autoencoder Neural Networks
PublikacjaA method developed for parametrization of EEG signals gathered from participants with acquired brain injuries is shown. Signals were recorded during therapeutic session consisting of a series of computer assisted exercises. Data acquisition was performed in a neurorehabilitation center located in Poland. The presented method may be used for comparing the performance of subjects with acquired brain injuries (ABI) who are involved...
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Exploring Relationships Between Data in Enterprise Information Systems by Analysis of Log Contents
PublikacjaEnterprise systems are inherently complex and maintaining their full, up-to-date overview poses a serious challenge to the enterprise architects’ teams. This problem encourages the search for automated means of discovering knowledge about such systems. An important aspect of this knowledge is understanding the data that are processed by applications and their relationships. In our previous work, we used application logs of an enterprise...
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Wiktoria Wojnicz dr hab. inż.
OsobyDSc in Mechanics (in the field of Biomechanics) - Lodz Univeristy of Technology, 2019 PhD in Mechanics (in the field of Biomechanics) - Lodz Univeristy of Technology, 2009 (with distinction) Publikacje z listy MNiSW (2009 - ) Wojnicz W., Wittbrodt E., Analysis of muscles' behaviour. Part I. The computational model of muscle. Acta of Bioengineering and Biomechanics, Vol. 11, No.4, 2009, p. 15-21 Wojnicz W., Wittbrodt E.,...