Search results for: :LEARNING - Bridge of Knowledge

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Search results for: :LEARNING

Search results for: :LEARNING

  • MANAGING LEARNING PROCESS WITH E-LEARNING TOOL

    This 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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  • Learning

    Journals

    ISSN: 2373-5082 , eISSN: 2373-5090

  • E-learning versus traditional learning - Polish case

    Publication

    - Year 2005

    E-learning jest współczesnym fenomenem, który pozwala na dostęp do kształcenia i treści edukacyjnych, niezależnie od czasu i miejsca, dla każdego użytkownika. E-learnig tworzy ogromne możliwości dla uczelni akademickich, organizacji, instytucji komercyjnych i szkoleniowych, dostarczając na żądanie kształcenia i szkoleń w wirtualnym środowisku. Student może stworzyć własny plan kształcenia, dostosowując go do swojej pracy i sytuacji...

  • Deep Learning

    Publication

    - Year 2021

    Deep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...

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  • Model-free and Model-based Reinforcement Learning, the Intersection of Learning and Planning

    Publication

    - Year 2022

    My doctoral dissertation is intended as the compound of four publications considering: structure and randomness in planning and reinforcement learning, continuous control with ensemble deep deterministic policy gradients, toddler-inspired active representation learning, and large-scale deep reinforcement learning costs.

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  • Deep Learning: A Case Study for Image Recognition Using Transfer Learning

    Publication

    - Year 2021

    Deep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...

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  • Deep learning in the fog

    In the era of a ubiquitous Internet of Things and fast artificial intelligence advance, especially thanks to deep learning networks and hardware acceleration, we face rapid growth of highly decentralized and intelligent solutions that offer functionality of data processing closer to the end user. Internet of Things usually produces a huge amount of data that to be effectively analyzed, especially with neural networks, demands high...

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  • Model szkolenia "Blended learning" z wykorzystaniem platformy Oracle I-learning.

    Publication

    - Year 2004

    W artykule zaproponowano modele organizacyjne szkoleń "blended learning", które pokazują możliwości współpracy firm prywatnych z instytucjami edukacyjnymi w dziedzinie e-learningu. W ramach wspólnego eksperymentu firm Oracle, Incenti S.A., WiedzaNet Sp. z o.o. oraz Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej w semestrze letnim roku akademickiego 2003/2004 udostępniony będzie kurs dla studentów Wydziału Inzynierii Lądowej...

  • Open source solution LMS for supporting e-learning/blended learning engineers

    Publication

    - Year 2005

    W artykule zaprezentowano darmowe systemy zarządzania kształceniem na odległość wspomagające e-learningowe/mieszane nauczanie inżynierów. Pierwszy system TeleCAD został opracowany w ramach projektu Leonardo da Vinci (1998-2001). System TeleCAD był propozycją w projekcie V Ramowy CURE (2003-2006). W roku 2003 dzięki projektowi Leonardo da Vinci EMDEL (2001-2005) Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej wybrało system...

  • Social learning in cluster initiatives

    Publication

    - Competitiveness Review - Year 2022

    Purpose – The purpose of the paper is to portray social learning in cluster initiatives (CIs), namely: 1) to explore, with the lens of the communities of practice (CoPs) theory, in what ways social learning occurs in CIs; 2) to discover how various CoPs emerge and evolve in CIs to facilitate a collective journey in their learning process. Subsequently, the authors address the research questions: In what ways does social learning...

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  • Neural networks and deep learning

    Publication

    - Year 2022

    In this chapter we will provide the general and fundamental background related to Neural Networks and Deep Learning techniques. Specifically, we divide the fundamentals of deep learning in three parts, the first one introduces Deep Feed Forward Networks and the main training algorithms in the context of optimization. The second part covers Convolutional Neural Networks (CNN) and discusses their main advantages and shortcomings...

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  • Online Learning Based on Prototypes

    Publication

    - Year 2014

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  • Distributed Learning with Data Reduction

    Publication

    - Year 2011

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  • Deep Learning Approaches in Histopathology

    Publication

    - Cancers - Year 2022

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  • e-Learning in Tourism Education

    Publication
    • N. Kalbaska
    • L. Cantoni

    - Year 2021

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  • Active learning na wykładach

    Events

    09-12-2024 09:00 - 09-12-2024 15:30

    Zapraszamy na szkolenie - Active learning na wykładach

  • Machine Learning and Deep Learning Methods for Fast and Accurate Assessment of Transthoracic Echocardiogram Image Quality

    Publication
    • W. Nazar
    • K. Nazar
    • L. Daniłowicz-Szymanowicz

    - Life - Year 2024

    High-quality echocardiogram images are the cornerstone of accurate and reliable measurements of the heart. Therefore, this study aimed to develop, validate and compare machine learning and deep learning algorithms for accurate and automated assessment of transthoracic echocardiogram image quality. In total, 4090 single-frame two-dimensional transthoracic echocardiogram...

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  • Learning & Memory

    Journals

    ISSN: 0143-7534

  • Adult Learning

    Journals

    ISSN: 1045-1595 , eISSN: 2162-4070

  • Open Learning

    Journals

    ISSN: 0268-0513 , eISSN: 1469-9958

  • For the Learning of Mathematics

    Journals

    ISSN: 0228-0671

  • Teaching & Learning

    Journals

    ISSN: 0887-9486

  • Vocations and Learning

    Journals

    ISSN: 1874-785X , eISSN: 1874-7868

  • Action Learning

    Journals

    ISSN: 1476-7333 , eISSN: 1476-7341

  • LEARNing Landscapes

    Journals

    ISSN: 1913-5688

  • Support for Learning

    Journals

    ISSN: 0268-2141 , eISSN: 1467-9604

  • E-Learning

    Journals

    ISSN: 1741-8887

  • Ubiquitous Learning

    Journals

    ISSN: 1835-9795

  • Learning Disabilities

    Journals

    ISSN: 1937-6928

  • Online Learning

    Journals

    ISSN: 1939-5256 , eISSN: 1092-8235

  • LEARNING & MEMORY

    Journals

    ISSN: 1072-0502 , eISSN: 1549-5485

  • MACHINE LEARNING

    Journals

    ISSN: 0885-6125 , eISSN: 1573-0565

  • LEARNING & BEHAVIOR

    Journals

    ISSN: 1543-4494 , eISSN: 1543-4508

  • LANGUAGE LEARNING

    Journals

    ISSN: 0023-8333 , eISSN: 1467-9922

  • Learning and Instruction

    Journals

    ISSN: 0959-4752

  • MANAGEMENT LEARNING

    Journals

    ISSN: 1350-5076 , eISSN: 1461-7307

  • LEARNING AND MOTIVATION

    Journals

    ISSN: 0023-9690 , eISSN: 1095-9122

  • Metacognition and Learning

    Journals

    ISSN: 1556-1623 , eISSN: 1556-1631

  • Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models

    Publication

    Breast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...

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  • Active Learning on Ensemble Machine-Learning Model to Retrofit Buildings Under Seismic Mainshock-Aftershock Sequence

    Publication

    This research presents an efficient computational method for retrofitting of buildings by employing an active learning-based ensemble machine learning (AL-Ensemble ML) approach developed in OpenSees, Python and MATLAB. The results of the study shows that the AL-Ensemble ML model provides the most accurate estimations of interstory drift (ID) and residual interstory drift (RID) for steel structures using a dataset of 2-, to 9-story...

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  • Lifelong Learning Idea in Architectural Education

    The 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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  • Revisiting Supervision for Continual Representation Learning

    Publication
    • D. Marczak
    • S. Cygert
    • T. Trzciński
    • B. Twardowski

    - Year 2024

    "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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  • Speech Analytics Based on Machine Learning

    Publication

    In this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...

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  • THE METHODS OF TEACHING / LEARNING STRUCTURAL MECHANICS

    Publication

    - Year 2024

    Structural mechanics is a key issue to study for engineers. A high rank and high social responsibility profession requires both a high graded and intuitive approach. The evolution of learning / teaching methodology follows the novel technical achievements of every decade. The aim remains the same: to produce a professional to perform advanced relevant analysis and safe, optimal structural design

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  • Collaborative Data Acquisition and Learning Support

    With the constant development of neural networks, traditional algorithms relying on data structures lose their significance as more and more solutions are using AI rather than traditional algorithms. This in turn requires a lot of correctly annotated and informative data samples. In this paper, we propose a crowdsourcing based approach for data acquisition and tagging with support for Active Learning where the system acts as an...

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  • Active Learning Based on Crowdsourced Data

    The paper proposes a crowdsourcing-based approach for annotated data acquisition and means to support Active Learning training approach. In the proposed solution, aimed at data engineers, the knowledge of the crowd serves as an oracle that is able to judge whether the given sample is informative or not. The proposed solution reduces the amount of work needed to annotate large sets of data. Furthermore, it allows a perpetual increase...

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  • Internet photogrammetry as a tool for e-learning

    Publication

    - Year 2015

    Along with Internet development, there were interactive applications which allow for remote sensing and photogrammetric analysis. An example of an application that can provide Earth images and make it possible to measure distances in these images is Google Earth. The authors, who have experience from 2001-2015 argue that it is possible and it is important to create more advanced photogrammetric network applications. In this there...

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  • Explainable machine learning for diffraction patterns

    Publication
    • S. Nawaz
    • V. Rahmani
    • D. Pennicard
    • S. P. R. Setty
    • B. Klaudel
    • H. Graafsma

    - Journal of Applied Crystallography - Year 2023

    Serial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...

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  • Towards Scalable Simulation of Federated Learning

    Federated 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...

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  • Note on universal algoritms for learning theory

    W 2001 Cucker i Smale zaproponowali nowe podejście do teorii uczenia się w oparciu o problematykę teorii aproksymacji.W 2005 i 2007 Bivev, Cohen, Dahmen, DeVore i Temlyakov opublikowali dwie prace z teorii uczenia się. W omawianej publikacji uogólniliśmy ich rezultaty jednocześnie upraszczając dowody.

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