Wyniki wyszukiwania dla: learning - MOST Wiedzy

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Wyniki wyszukiwania dla: learning

Wyniki wyszukiwania dla: learning

  • Spiral Search Grasshopper Features Selection with VGG19-ResNet50 for Remote Sensing Object Detection

    Publikacja
    • A. Stateczny
    • G. Uday Kiran
    • G. Bindu
    • K. Ravi Chythanya
    • K. Ayyappa Swamy

    - Remote Sensing - Rok 2022

    Remote sensing object detection plays a major role in satellite imaging and is required in various scenarios such as transportation, forestry, and the ocean. Deep learning techniques provide efficient performance in remote sensing object detection. The existing techniques have the limitations of data imbalance, overfitting, and lower efficiency in detecting small objects. This research proposes the spiral search grasshopper (SSG)...

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  • Will NILM Technology Replace Multi-Meter Telemetry Systems for Monitoring Electricity Consumption?

    Publikacja

    - ENERGIES - Rok 2023

    The estimation of electric power utilization, its baseload, and its heating, light, ventilation, and air-conditioning (HVAC) power component, which represents a very large portion of electricity usage in commercial facilities, are important for energy consumption controls and planning. Non-intrusive load monitoring (NILM) is the analytical method used to monitor the energy and disaggregate total electrical usage into appliance-related...

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  • The impact of the AC922 Architecture on Performance of Deep Neural Network Training

    Publikacja

    - Rok 2020

    Practical deep learning applications require more and more computing power. New computing architectures emerge, specifically designed for the artificial intelligence applications, including the IBM Power System AC922. In this paper we confront an AC922 (8335-GTG) server equipped with 4 NVIDIA Volta V100 GPUs with selected deep neural network training applications, including four convolutional and one recurrent model. We report...

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  • Civil liability for artificial intelligence products versus the sustainable development of CEECs: which institutions matter?

    Publikacja

    - Ruch Prawniczy, Ekonomiczny i Socjologiczny - Rok 2020

    The aim of this paper is to conduct a meta-analysis of the EU and CEECs civil liability institutions in order to find out if they are ready for the Artificial Intelligence (AI) race. Particular focus is placed on ascertaining whether civil liability institutions such as the Product Liability Directive (EU) or civil codes (CEECs) will protect consumers and entrepreneurs, as well as ensure undistorted competition. In line with the...

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  • Sathwik Prathapagiri

    Osoby

    Sathwik was born in 2000. In 2022, he completed his Master’s of Science in  Biological Sciences and Bachelor’s of Engineering in Chemical Engineering in an integrated dual degree program from Birla Institute Of Technology And Science, Pilani, India. During his final year, he worked as a research intern under Dr Giri P Krishnan at Bazhenov lab, University of California San Diego school of medicine to pursue his Master’s Thesis on...

  • ANALIZA STANU TECHNICZNEGO RUROCIĄGÓW: WODY PRZeMYSŁOWEJ I SOLANKI

    Pracę wykonano na zlecenie Przedsiębiorstwa Badawczo-Wdrożeniowego "HYDRO-POMP" Sp. z o.o. ul. Wróblewskiego 19, 93-578 Łódź. Wykonawcą zlecenia jest Politechnika Gdańska, Wydział Chemiczny, Katedra Elektrochemii, Korozji i Inżynierii Materiałowej, 80-233 Gdańsk, ul. G. Narutowicza 11/12. Celem pracy była analiza stanu technicznego i badania dwóch rurociągów: solanki oraz wody przemysłowej. Badania wykonywano w warunkach terenowych...

  • MOST Wiedzy jako narzędzie promocji otwartych zasobów nauki

    Rośnie znaczenie wiedzy zgromadzonej w różnego rodzaju systemach, w tym w kursach on-line. Połączenie systemów je przetwarzających z Internetem w znaczącym stopniu usprawniło rozprzestrzenianie informacji i zwiększyło jej dostępność. Coraz szersze uznanie zyskują ruchy Otwartego Dostępu (ang. Open Access). Politechnika Gdańska w ramach projektu Multidyscyplinarny Otwarty System Transferu Wiedzy – MOST Wiedzy buduje platformę o...

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  • QUEUE I

    Wydarzenia

    26-09-2022 10:12 - 30-09-2022 10:12

    Faculty of Applied Physics and Mathematics of Gdańsk Tech invites international students to the next summer school - Quantum and Molecules I (QUEUE I), organized within the ScienceApp project.

  • ART WORKSHOP PLEIN AIR

    Kursy Online
    • J. Buczkowski
    • E. Urwanowicz
    • D. Krechowicz
    • A. Wancław

    ART WORKSHOP PLEIN AIR   Outdoor classes in the field of painting for students of the first year of the Faculty of Architecture are aimed at shaping basic painting skills. Students continue to learn the basics of the tempera painting technique, which they learned in the second semester. Learning the basics of the painting workshop is carried out by looking for combinations of forms, mutual color relationships and the influence...

  • Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network

    Publikacja

    - Scalable Computing: Practice and Experience - Rok 2024

    COVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...

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  • Online sound restoration system for digital library applications

    Audio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...

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  • Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions

    Publikacja

    - Rok 2018

    With the technology advancements in smart home sector, voice control and automation are key components that can make a real difference in people's lives. The voice recognition technology market continues to involve rapidly as almost all smart home devices are providing speaker recognition capability today. However, most of them provide cloud-based solutions or use very deep Neural Networks for speaker recognition task, which are...

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  • Experimental determination of general characteristic of internal combustion engine using mobile test bench connected via Power Take-Off unit

    The general characteristics of the engine include information about the regions of the engine's operating area that are most efficient, where specific fuel consumption reaches the smallest values. Economic operation based on those characteristics can contribute to a significant reduction of fuel consumption and consequently less pollutant emissions and lower costs. The paper presents an experimental method of determination of general...

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  • Long Distance Vital Signs Monitoring with Person Identification for Smart Home Solutions

    Publikacja

    - Rok 2018

    Abstract— Imaging photoplethysmography has already been proved to be successful in short distance (below 1m). However, most of the real-life use cases of measuring vital signs require the system to work at longer distances, to be both more reliable and convenient for the user. The possible scenarios that system designers must have in mind include monitoring of the vital signs of residents in nursing homes, disabled people, who...

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  • Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting

    Publikacja

    - Resources-Basel - Rok 2022

    Forecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...

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  • Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks

    Age 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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  • Energy-Aware Scheduling for High-Performance Computing Systems: A Survey

    Publikacja

    High-performance computing (HPC), according to its name, is traditionally oriented toward performance, especially the execution time and scalability of the computations. However, due to the high cost and environmental issues, energy consumption has already become a very important factor that needs to be considered. The paper presents a survey of energy-aware scheduling methods used in a modern HPC environment, starting with the...

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  • An Automated Method for Biometric Handwritten Signature Authentication Employing Neural Networks

    Publikacja

    Handwriting biometrics applications in e-Security and e-Health are addressed in the course of the conducted research. An automated graphomotor analysis method for the dynamic electronic representation of the handwritten signature authentication was researched. The developed algorithms are based on dynamic analysis of electronically handwritten signatures employing neural networks. The signatures were acquired with the use of the...

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  • Semantic segmentation training using imperfect annotations and loss masking

    One of the most significant factors affecting supervised neural network training is the precision of the annotations. Also, in a case of expert group, the problem of inconsistent data annotations is an integral part of real-world supervised learning processes, well-known to researchers. One practical example is a weak ground truth delineation for medical image segmentation. In this paper, we have developed a new method of accurate...

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  • Metal–Organic Frameworks (MOFs) for Cancer Therapy

    Publikacja
    • M. Saeb
    • N. Rabiee
    • M. Mozafari
    • F. Verpoort
    • L. G. Voskressensky
    • R. Luque

    - Materials - Rok 2021

    MOFs exhibit inherent extraordinary features for diverse applications ranging from catalysis, storage, and optics to chemosensory and biomedical science and technology. Several procedures including solvothermal, hydrothermal, mechanochemical, electrochemical, and ultrasound techniques have been used to synthesize MOFs with tailored features. A continued attempt has also been directed towards functionalizing MOFs via “post-synthetic...

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