Extending Dataset with Data Augmentation

Sergey L. Gladkiy

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21 Dec 2020CPOL4 min read

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In this article, we’ll see how the same result can be achieved by data augmentation.

Here we'll provide a very short introduction to the data augmentation technique. Then we select appropriate methods of augmentation suitable for our dataset. Then we provide and explain the Python code for implementing the augmentation algorithms. And finally, we demonstrate the resulting image examples.

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This article is part of the series 'Real-time AI Pest Elimination on Edge Devices ◁ Prev View All Next ▷

License

This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

Written By

Sergey L. Gladkiy

Team Leader VIPAKS

Russian Federation

EDUCATION:

Master’s degree in Mechanics.

PhD degree in Mathematics and Physics.

PROFESSIONAL EXPERIENCE:

15 years’ experience in developing scientific programs
(C#, C++, Delphi, Java, Fortran).

SCIENTIFIC INTERESTS:

Mathematical modeling, symbolic computer algebra, numerical methods, 3D geometry modeling, artificial intelligence, differential equations, boundary value problems.

Extending Dataset with Data Augmentation

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