Wyniki wyszukiwania dla: BIG DATA DEEP LEARNING REMOTE MEDICAL DIAGNOSTIC - MOST Wiedzy

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Wyniki wyszukiwania dla: BIG DATA DEEP LEARNING REMOTE MEDICAL DIAGNOSTIC

Wyniki wyszukiwania dla: BIG DATA DEEP LEARNING REMOTE MEDICAL DIAGNOSTIC

  • Data augmentation for improving deep learning in image classification problem

    Publikacja

    These days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...

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  • Deep Learning Basics 2023/24

    Kursy Online
    • K. Draszawka

    A course about the basics of deep learning intended for students of Computer Science. It includes an introduction to supervised machine learning, the architecture of basic artificial neural networks and their training algorithms, as well as more advanced architectures (convolutional networks, recurrent networks, transformers) and regularization and optimization techniques.

  • Review of the Complexity of Managing Big Data of the Internet of Things

    Publikacja

    - COMPLEXITY - Rok 2019

    Tere is a growing awareness that the complexity of managing Big Data is one of the main challenges in the developing feld of the Internet of Tings (IoT). Complexity arises from several aspects of the Big Data life cycle, such as gathering data, storing them onto cloud servers, cleaning and integrating the data, a process involving the last advances in ontologies, such as Extensible Markup Language (XML) and Resource Description...

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  • Deep Learning

    Publikacja

    - Rok 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-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data

    Publikacja

    - IEEE Journal of Translational Engineering in Health and Medicine-JTEHM - Rok 2024

    The field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...

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  • Deep neural networks for data analysis

    Kursy Online
    • K. Draszawka

    The aim of the course is to familiarize students with the methods of deep learning for advanced data analysis. Typical areas of application of these types of methods include: image classification, speech recognition and natural language understanding. Celem przedmiotu jest zapoznanie studentów z metodami głębokiego uczenia maszynowego na potrzeby zaawansowanej analizy danych. Do typowych obszarów zastosowań tego typu metod należą:...

  • Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models

    Publikacja
    • A. Pereira García
    • L. Porwol
    • A. Ojo

    - Rok 2023

    High-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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  • Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning

    Publikacja

    - Rok 2023

    In this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....

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  • Harmony Search for Data Mining with Big Data

    Publikacja

    - Rok 2016

    In this paper, some harmony search algorithms have been proposed for data mining with big data. Three areas of big data processing have been studied to apply new metaheuristics. The first problem is related to MapReduce architecture that can be supported by a team of harmony search agents in grid infrastructure. The second dilemma involves development of harmony search in preprocessing of data series before data mining. Moreover,...

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  • Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems

    Publikacja

    - COMPLEXITY - Rok 2019

    Te 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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