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

  • Big Data in Regenerative Urban Design

    Why the use of Big Data in regenerative planning matters? The aim of this chapter is to study under what conditions Big Data can be integrated into regenerative design and sustainable planning? Authors seek to answer how – when related to the ecosystem and to human activities – Big Data can be used to: • both shape policies that support the development of regenerative human settlements, • support restorative design for practitioners...

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  • Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning

    Publikacja
    • A. Nabożny
    • B. Balcerzak
    • A. Wierzbicki
    • M. Morzy
    • M. Chlabicz

    - JMIR Medical Informatics - Rok 2021

    Methods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...

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  • The Use of Big Data in Regenerative Planning

    With the increasing significance of Big Data sources and their reliability for studying current urban development processes, new possibilities have appeared for analyzing the urban planning of contemporary cities. At the same time, the new urban development paradigm related to regenerative sustainability requires a new approach and hence a better understanding of the processes changing cities today, which will allow more efficient...

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  • On the impact of Big Data and Cloud Computing on a scalable multimedia archiving system

    Multimedia Archiver (MA) is a system build upon the promise and fascination of the possibilities emerging from cloud computing and big data. We aim to present and describe how the Multimedia Archiving system works for us to record, put in context and allow a swift access to large amounts of data. We introduce the architecture, identified goals and needs taken into account while designing a system processing data with Big Data...

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  • Big Data Analytics for ICT Monitoring and Development

    Publikacja

    - Rok 2017

    The expanded growth of information and communication technology has opened new era of digitization which is proving to be a great challenge for researchers and scientists around the globe. The utmost paradigm is to handle and process the explosion of data with minimal cost and discover relevant hidden information in the least amount of time. The buzz word “BIG DATA” is a widely anticipated term with the potential to handle heterogeneous,...

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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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  • Neural networks and deep learning

    Publikacja

    - Rok 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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  • Analiza danych typu Big Data 2022/23

    Kursy Online
    • P. Weichbroth
    • W. Waloszek

    The aim of the course is to familiarize students with the methods of storing and analysis of big data. Practical tools for these tasks are presented.

  • Deep Learning: A Case Study for Image Recognition Using Transfer 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 CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY

    The paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...

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