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Wyniki wyszukiwania dla: MACHINE LEARNING, DEEP NEURAL NETWORKS, CEREBRAL MICROBLEEDS, CMB DETECTION, MR IMAGES
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e-Learning - user's guide for students
Kursy Onlinee-Learning - user's guide for students
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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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Toward Robust Pedestrian Detection With Data Augmentation
PublikacjaIn this article, the problem of creating a safe pedestrian detection model that can operate in the real world is tackled. While recent advances have led to significantly improved detection accuracy on various benchmarks, existing deep learning models are vulnerable to invisible to the human eye changes in the input image which raises concerns about its safety. A popular and simple technique for improving robustness is using data...
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Electrical and noise responses of carbon nanotube networks enhanced by UV light for nitrogen dioxide sensing
Dane BadawczeNetworks consisting of randomly oriented carbon nanotubes (CNN) were investigated toward nitrogen dioxide detection by means of electrical and low-frequency noise measurements. UV-activation of CNN layers improved gas sensitivity and reduced the limit of detection, especially by employing 275 nm-LED. This data set includes DC resistance measurements...
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Prediction of Sorption Processes Using the Deep Learning Methods (Long Short-Term Memory)
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Deep learning model for automated assessment of lexical stress of non-native english speakers
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OBTAINING FLUID FLOW PATTERN FOR TURBINE STAGE WITH NEURAL MODEL.
PublikacjaIn the paper possibility of applying neural model to obtaining patterns of proper operation for fluid flow in turbine stage for fluid-flow diagnostics is discussed. Main differences between Computational Fluid Dynamics (CFD) solvers and neural model is given, also limitations and advantages of both are considered. Time of calculations of both methods was given, also possibilities of shortening that time with preserving the accuracy...
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublikacjaDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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Scene Segmentation Basing on Color and Depth Images for Kinect Sensor
PublikacjaIn this paper we propose a method for segmenting single images from Kinect sensor by considering both color and depth information. The algorithm is based on a series of edge detection procedures designed for particular features of the scene objects. RGB and HSV color planes are separately analyzed in the first step with Canny edge detector, resulting in overall color edges mask. In depth images both clear boundaries and smooth...
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublikacjaAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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Cleaner energy for sustainable future using hybrid photovoltaics-thermoelectric generators system under non-static conditions using machine learning based control technique
PublikacjaIn addition to the load demand, the temperature difference between the hot and cold sides of the thermoelectric generator (TEG) module determines the output power for thermoelectric generator systems. Maximum power point tracking (MPPT) control is needed to track the optimal global power point as operating conditions change. The growing use of electricity and the decline in the use of fossil fuels have sparked interest in photovoltaic-TEG...
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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublikacjaTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
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Machine Learning for Control Systems Security of Industrial Robots: a Post-covid-19 Overview
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Likelihood of Transformation to Green Infrastructure Using Ensemble Machine Learning Techniques in Jinan, China
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Machine Learning Methods in Damage Prediction of Masonry Development Exposed to the Industrial Environment of Mines
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Lifelong Learning Idea in Architectural Education
PublikacjaThe recent advances in IT and technology are forcing changes in the approach to educating society. In the 20th century, life-long learning was understood as educating adults in order to improve their occupational qualifications. Life-long learning allows the needs of the present-day world to be addressed through providing the individual with education at every stage of his/her life various forms. The search for a new model...
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Ensembling noisy segmentation masks of blurred sperm images
PublikacjaBackground: Sperm tail morphology and motility have been demonstrated to be important factors in determining sperm quality for in vitro fertilization. However, many existing computer-aided sperm analysis systems leave the sperm tail out of the analysis, as detecting a few tail pixels is challenging. Moreover, some publicly available datasets for classifying morphological defects contain images limited only to the sperm head. This...
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Using Disparity Map for Moving Object Position Estimation in Pan Tilt Camera Images
PublikacjaIn this paper we present the algorithm for rapid moving object position estimation in an images acquired from pan tilt camera. Detection of a moving object in a image acquired from a moving camera might be quite challenging. Standard methods that relay on analyzing two consecutive frames are not applicable due to the changing background. To overtake this problem we decided to evaluate the possibility of calculating a disparity...
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Broken Rotor Symptons in the Sensorless Control of Induction Machine
PublikacjaInverter fed sensorless controlled variable speed drives with induction machine are widely used in the industry applications, also in wind power generation and electric vehicles. On-line self diagnostic systems implementation is needed for early stage fault detection and avoiding a critical fault. Diagnostic algorithms in modern DSP-based controllers can operate simultaneously with control system functions. In the closed-loop controlled...
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Social media for e-learning of citizens in smart city
PublikacjaThe rapid development of social media can be applied for citizens’ e-learning in a smart city. Big cities have to cope with several open issues like a growing population or a traffic congestion. Especially, a home and public space is supposed to be used in more efficient way. Sustainable homes and buildings can be planned with using some modern techniques. Even currently, there is a huge problem with a lack of key resources like...
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Adaptive Method of Raster Images Compression and Examples of Its Applications in the Transport Telematic Systems
PublikacjaThe paper presents a concept and exemplary application of an adaptive method of compression of raster images which may be applied, i.a. in ITS systems. The described method allows to improve the efficiency of systems belonging to ITS category, which require transmission of large volumes of image data through telecommunications networks. The concept of the adaptive method of compression of raster images described in the paper uses...
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A study of nighttime vehicle detection algorithms
Dane BadawczeThis dataset is from my master's thesis "A study of nighttime vehicle detection algorithms". It contains both raw data and preprocessed dataset ready to use. In the pictures below you can see how images were annotated.
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Modeling the Networks - ed. 2021/2022
Kursy OnlineThe goal of this course is to present optimization problems for road networks, where the road network is a set of n distinct lines, or n distinct (open or closed) line segments, in the plane, such that their union is a connected region.
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Pupil detection supported by Haar feature based cascade classifier for two-photon vision examinations
PublikacjaThe aim of this paper is to present a novel method, called Adaptive Edge Detection (AED), of extraction of precise pupil edge coordinates from eye image characterized by reflections of external illuminators and laser beams. The method is used for monitoring of pupil size and position during psychophysical tests of two-photon vision performed by dedicated optical set-up. Two-photon vision is a new phenomenon of perception of short-pulsed...
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Modelling changes in the energy efficiency of buildings using neural networks on the example of Zielona Góra
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Prediction of Early Childhood Caries Based on Single Nucleotide Polymorphisms Using Neural Networks
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Application of artificial neural networks (ANN) as multiple degradation classifiers in thermal and flow diagnostics
PublikacjaPrzedyskutowano problem zwiększenia dokładności rozpoznawania wielokrotnych degradacji eksploatacyjnych urządzeń składowych dużych obiektów energetycznych. Zastosowani sieć neuronową (SSN) o skokowych funkcjach przejścia. Sprawdzono możliwości przyspieszenia treningu sieci neuronowych. Zastosowano modułową metodę budowy SSN, polegającą na dedykowaniu pojedynczej sieci do rozpoznawania tylko jednego typu degradacji.
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Accidental wow defect evaluation using sinusoidal analysis enhanced by artificial neural networks
PublikacjaArtykuł przedstawia metodę do wyznaczania charakterystyki pasożytniczych modulacji częstotliwości (kołysanie) obecnych w archiwalnych nagraniach dźwiękowych. Prezentowane podejście wykorzystuje śledzenie zmian sinusoidalnych komponentów dźwięku które odzwierciedlają przebieg kołysania. Analiza sinusoidalna wykorzystana jest do ekstrakcji składowych tonalnych ze zniekształconych nagrań dźwiękowych. Dodatkowo, w celu zwiększenia...
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublikacjaThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublikacjaThe Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...
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Edyta Gołąb-Andrzejak dr hab.
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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublikacjaControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
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Knowledge sharing and knowledge hiding in light of the mistakes acceptance component of learning culture- knowledge culture and human capital implications
PublikacjaPurpose: This study examines the micromechanisms of how knowledge culture fosters human capital development. Method: An empirical model was developed using the structural equation modeling method (SEM) based on a sample of 321 Polish knowledge workers employed in different industries. Findings: This study provides direct empirical evidence that tacit knowledge sharing supports human capital, whereas tacit knowledge hiding does...
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Modelling in machine design (PG_00057377)
Kursy Onlinegoal of the subject is to show how simple enginnering models reflect the reality and how contemporary FEM calulations can illustrate the operation of machine elements
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Temporal Satellite Images in The Process of Automatic Efficient Detection of Changes of the Baltic Sea Coastal Zone
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MANAGING LEARNING PROCESS WITH E-LEARNING TOOL
PublikacjaThis article presents one possibility to employ Moodle, the free e-Leaning platform, to organize learning understood as a process. Behavioral approach and application to massive courses are assumed. A case study is presented, where the introduction of Moodle resulted in better student performance in homework
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Acoustical images of the Gulf of Gdansk
PublikacjaAcoustic images of seabed are of interest to specialists in the field of marine engineering, marine navigation, marine archeology, hydrogeology, etc. New technolo gies based on use of elastic waves, predominantly acoustic waves that allow detecting complexity of geometric forms of seabed, ensure progress in studying the bathymetric structure of seafloor. Use of parametric sources of waves generated...
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Digital fingerprinting for color images based on the quaternion encryption scheme
PublikacjaIn this paper we present a new quaternion-based encryption technique for color images. In the proposed encryption method, images are written as quaternions and are rotated in a three-dimensional space around another quaternion, which is an encryption key. The encryption process uses the cipher block chaining (CBC) mode. Further, this paper shows that our encryption algorithm enables digital fingerprinting as an additional feature....
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Polymodal Method of Improving the Quality of Photogrammetric Images and Models
PublikacjaPhotogrammetry using unmanned aerial vehicles has become very popular and is already commonly used. The most frequent photogrammetry products are an orthoimage, digital terrain model and a 3D object model. When executing measurement flights, it may happen that there are unsuitable lighting conditions, and the flight itself is fast and not very stable. As a result, noise and blur appear on the images, and the images themselves can...
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Visual Features for Endoscopic Bleeding Detection
PublikacjaAims: To define a set of high-level visual features of endoscopic bleeding and evaluate their capabilities for potential use in automatic bleeding detection. Study Design: Experimental study. Place and Duration of Study: Department of Computer Architecture, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, between March 2014 and May 2014. Methodology: The features have...
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Traffic Remapping Attacks in Ad Hoc Networks
PublikacjaAd hoc networks rely on the mutual cooperation of stations. As such, they are susceptible to selfish attacks that abuse network mechanisms. Class-based QoS provisioning mechanisms, such as the EDCA function of IEEE 802.11, are particularly prone to traffic remapping attacks, which may bring an attacker better QoS without exposing it to easy detection. Such attacks have been studied in wireless LANs, whereas their impact in multihop...
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Application of Feed Forward Neural Networks for Modeling of Heat Transfer Coefficient During Flow Condensation for Low and High Values of Saturation Temperatur
PublikacjaMost of the literature models for condensation heat transfer prediction are based on specific experimental parameters and are not general in nature for applications to fluids and non-experimental thermodynamic conditions. Nearly all correlations are created to predict data in normal HVAC conditions below 40°C. High temperature heat pumps operate at much higher parameters. This paper aims to create a general model for the calculation...
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Exploiting multi-interface networks: Connectivity and Cheapest Paths
PublikacjaLet G = (V,E) be a graph which models a set of wireless devices (nodes V) that can communicate by means of multiple radio interfaces, according to proximity and common interfaces (edges E). The problem of switching on (activating) the minimum cost set of interfaces at the nodes in order to guarantee the coverage of G was recently studied. A connection is covered (activated) when the endpoints of the corresponding edge share at...
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CANCER DETECTION AND PREVENTION
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Biomolecular Detection and Quantification
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Electromagnetic Modeling of Microstrip Elements Aided with Artificial Neural Network
PublikacjaThe electromagnetic modeling principle aided withartificial neural network to designing the microwave widebandelements/networks prepared in microstrip technology is proposedin the paper. It is assumed that the complete information is knownfor the prototype design which is prepared on certain substratewith certain thickness and electric permittivity. The longitudinaland transversal dimensions of new design...
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Deep learning based segmentation using full wavefield processing for delamination identification: A comparative study
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Paweł Burdziakowski dr inż.
Osobydr inż. Paweł Burdziakowski jest specjalista w zakresie fotogrametrii i teledetekcji lotniczej niskiego pułapu, nawigacji morskiej i lotniczej. Jest również licencjonowanym instruktorem lotniczym oraz programistą. Głównymi obszarami zainteresowania jest fotogrametria cyfrowa, nawigacja platform bezzałogowych oraz systemy bezzałogowe, w tym lotnicze, nawodne, podwodne. Prowadzi badania w zakresie algorytmów i metod poprawiających...
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Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional Study
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SELECTED PROBLEMS OF MACHINE DYNAMICS (2024)
Kursy OnlineThe course is devoted towards lectures assocuated with the novel issues of machine and structures dynamics. The following lectures will be given during the SPMD course: - introduction to selected problems of machine dynamics, - definition of the machine and structure working environment, - internal and external loads on machines and structures, - dynamics of machines and structures, - strength of machines and structures, - special...