Real-time AI Pest Elimination on Edge Devices: Getting Started

Sergey L. Gladkiy

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3 Mar 2021CPOL4 min read

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In this article, we compared two DNN types we can use to detect pests: detectors and classifiers.

Here, we state the problem of pest elimination in terms of using AI and DNN. We then suggest two possible solutions: 1 – using pretrained SSD models to detect cats, sheep and others; 2 – using MD and train our own DNN to detect ‘nonstandard’ pests such as moose. Finally, we provide a short outline of the series and state the tools for developing: Python, OpenCV, Caffe.

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This article is part of the series 'Real-time AI Pest Elimination on Edge Devices 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 Pest Elimination on Edge Devices: Getting Started

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