Single Spike Neural Network Model for Superficial Environment Classification for Mobile Robot Navigation

Single Spike Neural Network Model for Superficial Environment Classification for Mobile Robot Navigation

In this work, a single Semi-Recurrent Spike Neural Network (SRSNN) supervised learning method based on time coding is proposed to classify visual terrain encountered by the mobile robot. To this end, the features are extracted using the Local Binary Pattern (LBP) method. Then, the SRSNN is trained...

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Bibliographic Details
Main Authors: Zhraa Issam Ibrahim, Nadia Adnan Shiltagh Al-Jamali
Format: Article
Language:English
Published: University of Baghdad 2024-04-01
Series:Journal of Engineering
Subjects:
Single Spike Neural Network(SSNN)
Terrain Classification
Mobile Robots
Online Access:https://joe.uobaghdad.edu.iq/index.php/main/article/view/2308

Internet

https://joe.uobaghdad.edu.iq/index.php/main/article/view/2308

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