DATA AUGMENTATION FOR NEURAL NETWORK OPTIMAL GENERALIZATION

Journal Title: International scientific journal Science and Innovation - Year 2023, Vol 2, Issue 3

Abstract

To expand the size of a real dataset, data augmentation techniques artificially create various versions of the original dataset. Following their application, many techniques and methods have demonstrated an improvement in the precision of machine learning models. It serves as a regularizer during machine learning model training and aids in lowering overfitting. This article will cover the application of data augmentation techniques based on different noise types that shows improved neural network performance.

Authors and Affiliations

Abdurashitova Muniskhon

Keywords

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  • EP ID EP714426
  • DOI 10.5281/zenodo.7739565
  • Views 56
  • Downloads 0

How To Cite

Abdurashitova Muniskhon (2023). DATA AUGMENTATION FOR NEURAL NETWORK OPTIMAL GENERALIZATION. International scientific journal Science and Innovation, 2(3), -. https://europub.co.uk/articles/-A-714426