Training a DNN

Sergey L. Gladkiy

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22 Dec 2020CPOL4 min read

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In this article, we’ll discuss training our DNN classifier with the augmented dataset.

Here we'll suggest a DNN model for detecting a moose on images. Then we'll provide Python code to generate input data for training a DNN with Caffe. Then we explain how to launch Caffe. Finally, we demonstrate the training log and explain the results.

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

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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.

Training a DNN

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