Filtry
wszystkich: 165
wybranych: 136
Wyniki wyszukiwania dla: GRAPHIC TRAIN TIMETABLE
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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublikacjaAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
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Emission of 1.3–10 nm airborne particles from brake materials
PublikacjaOperation of transport vehicle brakes makes a significant contribution to airborne particulate matter in urban areas, which is subject of numerous studies due to the environmental concerns. We investigated the presence and number fractions of 1.3–10 nm airborne particles emitted from a low-metallic car brake material (LM), a non-asbestos organic car brake material (NAO) and a train brake cast iron against a cast iron. Particles...
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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublikacjaTo 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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Mobile satellite measurements in designing and exploitation of rail roads
PublikacjaThe article presents a summary of several years (2009-2015) of studies on the application of mobile satellite Global Navigation Satellite Systems (GNSS) measurements in the field of designing and operation of railways. These studies have been conducted by an interdisciplinary research team from the Gdansk University of Technology and the Gdynia Maritime University. Mobile satellite GNSS measurements are taken during a ride (through...
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BP-EVD: Forward Block-Output Propagation for Efficient Video Denoising
PublikacjaDenoising videos in real-time is critical in many applications, including robotics and medicine, where varying light conditions, miniaturized sensors, and optics can substantially compromise image quality. This work proposes the first video denoising method based on a deep neural network that achieves state-of-the-art performance on dynamic scenes while running in real-time on VGA video resolution with no frame latency. The backbone...
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Automatic singing quality recognition employing artificial neural networks
PublikacjaCelem artykułu jest udowodnienie możliwości automatycznej oceny jakości technicznej głosów śpiewaczych. Pokrótce zaprezentowano w nim stworzoną bazę danych głosów śpiewaczych oraz zaimplementowane parametry. Przy pomocy sztucznych sieci neuronowych zaprojektowano system decyzyjny, który oceniono w pięciostopniowej skali jakość techniczną głosu. Przy pomocy metod statystycznych udowodniono, że wyniki generowane przez ten system...
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Between autonomy and paternalism: Attitudes of nursing personnel towards Jehovah’s Witnesses’ refusal of blood transfusion
PublikacjaObjectives: The study describes the attitudes of Polish nursing personnel towards Jehovah’s Witnesses’ (JWs’) refusal to receive blood and blood products.Methods: We developed an online survey assessing nurses’ knowledge and attitudes towards JWs’ refusal of blood transfusion in a life-threatening condition. It also examined nurses’ attitudes towards ethical and legal issues associated with JWs’ refusal of bloodtransfusions....
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublikacjaHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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Resource constrained neural network training
PublikacjaModern applications of neural-network-based AI solutions tend to move from datacenter backends to low-power edge devices. Environmental, computational, and power constraints are inevitable consequences of such a shift. Limiting the bit count of neural network parameters proved to be a valid technique for speeding up and increasing efficiency of the inference process. Hence, it is understandable that a similar approach is gaining...
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Personalized nutrition in ageing society: redox control of major-age related diseases through the NutRedOx Network (COST Action CA16112)
PublikacjaA healthy ageing process is important when it is considered that one-third of the population of Europe is already over 50 years old, although there are regional variations. This proportion is likely to increase in the future, and maintenance of vitality at an older age is not only an important measure of the quality of life but also key to participation and productivity. So, the binomial “nutrition and ageing” has different aspects...
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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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Potential reduction of traffic noise by the means of increased fleet of electric vehicles using a combination of low-noise tyres and low-noise road surfaces
PublikacjaIn the future, the number of zero-emission vehicles like electric and plug-in hybrid vehicles (in electric mode) is expected to be a substantial part of the vehicle fleet. In Norway, such vehicles already account for approximately 20 % of all new cars sold. Since these vehicles emit negligible noise related to the power-train, the tyre/road noise is the dominating noise source. In the LEO project, tyres designed for such cars have...
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Assessing the attractiveness of human face based on machine learning
PublikacjaThe attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...
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VREA PROJECT - A DIGITAL CURATOR FOR ARCHITECTURE AND DIGITAL PERSPECTIVES FOR HERITAGE MANAGEMENT AND ENHANCEMENT
PublikacjaThinking about architectural education, one must face the challenges of the ever-changing and digital world and bear in mind the figure of the architect of the future - the curator of digital data. Nowadays the aim is to train specialists who know how to manage the production of digital products and are able to face the challenges of digital change in the field of architecture and architectural heritage management. Virtual Reality...
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Machine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects
PublikacjaMachine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects Hammed A. Mojeed & Rafal Szlapczynski Conference paper First Online: 14 September 2023 161 Accesses Part of the Lecture Notes in Computer Science book series (LNAI,volume 14125) Abstract Software development project requires proper planning to mitigate risk and...
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Research project BRIK: development of an innovative method for determining the precise trajectory of a railway vehicle
PublikacjaIn the paper the essential assumptions regarding a research project implemented by a consortium of Gdansk University of Technology and Gdynia Maritime University are presented. The project has been commissioned by National Center of Research and Development with cooperation with Polish Railways (PKP Polskie Linie Kolejowe S.A.). The project is focused in implementation of modern measurement techniques using Global Navigation Positioning...
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublikacjaBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublikacjaNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublikacjaWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Towards Scalable Simulation of Federated Learning
PublikacjaFederated learning (FL) allows to train models on decentralized data while maintaining data privacy, which unlocks the availability of large and diverse datasets for many practical applications. The ongoing development of aggregation algorithms, distribution architectures and software implementations aims for enabling federated setups employing thousands of distributed devices, selected from millions. Since the availability of...