Wyniki wyszukiwania dla: MACHINE LEARNING, XGBOOST

• MACHINE LEARNING

  Czasopisma

  ISSN: 0885-6125 , eISSN: 1573-0565

• Speech Analytics Based on Machine Learning

  Publikacja

  • G. Korvel
  • A. Kurowski
  • B. Kostek
  • A. Czyżewski

  - Rok 2019

  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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• Explainable machine learning for diffraction patterns

  Publikacja

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

  - Journal of Applied Crystallography - Rok 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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• Machine Learning Techniques in Concrete Mix Design

  Publikacja

  • P. Ziółkowski
  • M. Niedostatkiewicz

  - Materials - Rok 2019

  Concrete mix design is a complex and multistage process in which we try to find the best composition of ingredients to create good performing concrete. In contemporary literature, as well as in state-of-the-art corporate practice, there are some methods of concrete mix design, from which the most popular are methods derived from The Three Equation Method. One of the most important features of concrete is compressive strength, which...

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• Introduction to the special issue on machine learning in acoustics

  Publikacja

  • Z. Michalopoulou
  • P. Gerstoft
  • B. Kostek
  • M. A. Roch

  - Journal of the Acoustical Society of America - Rok 2021

  When we started our Call for Papers for a Special Issue on “Machine Learning in Acoustics” in the Journal of the Acoustical Society of America, our ambition was to invite papers in which machine learning was applied to all acoustics areas. They were listed, but not limited to, as follows: • Music and synthesis analysis • Music sentiment analysis • Music perception • Intelligent music recognition • Musical source separation • Singing...

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• Machine Learning and Electronic Noses for Medical Diagnostics

  Publikacja

  • W. Wojnowski
  • K. Kalinowska

  - Rok 2021

  The need for noninvasive, easy-to-use, and inexpensive methods for point-of-care diagnostics of a variety of ailments motivates researchers to develop methods for analyzing complex biological samples, in particular human breath, that could aid in screening and early diagnosis. There are hopes that electronic noses, that is, devices based on arrays of semiselective or nonselective chemical sensors, can fill this niche. Electronic...

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• Concrete mix design using machine learning

  Publikacja

  • P. Ziółkowski
  • M. Niedostatkiewicz

  - Rok 2019

  Designing a concrete mix is a process of synthesizing many components, it is not a simple process and requires extensive technical knowledge. The design process itself focuses on obtaining the required strength of concrete. Very often designing a concrete mix takes into account the need to maintain the proper water-demand and frost-resistance features. The parameters that influence the concrete class most significantly are the...

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• Foundations and Trends in Machine Learning

  Czasopisma

  ISSN: 1935-8237 , eISSN: 1935-8245

• Machine Learning and Knowledge Extraction

  Czasopisma

  eISSN: 2504-4990

• Machine Learning-Science and Technology

  Czasopisma

  eISSN: 2632-2153