Real-time AI Person Detection on Edge Devices: Selecting Deep Learning Models

Sergey L. Gladkiy

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6 Oct 2020CPOL4 min read

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In this article, we’ll discuss the pros and cons of the existing DNN approaches and select a pre-trained model for further experimentation.

Here we'll select(for further work) two SSD models, one based on MobileNet and another one based on SqueezeNet.

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This article is part of the series 'Realtime AI Person Detection 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.

Real-time AI Person Detection on Edge Devices: Selecting Deep Learning Models

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