Title
An Empirical Analysis of 3D Image Processing by using Machine Learning-Based Input Processing for Man-Machine Interaction
Date Issued
01 January 2022
Access level
metadata only access
Resource Type
conference paper
Author(s)
Narang P.
Taufikin
Bangare S.L.
Valderrama-Zapata C.
Jaiswal S.
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
The 'human-robot interface' or HRI provides multiple assistance services in a variety of real-time applications. In robotic devices, the notion of object classification by digital visualisation is predicated on the converging of a 'three-dimensional (3D)' image into a plane-based representation. During the convergence process, the projectors in multiple planes are mistaken, resulting in identification mistakes. The information processing approach, which is based on the result showed, can lessen these misidentifications in object identification. The combining indexes are found by seeing and extending the input image in all conceivable directions. A machine learning technique is utilised to ways that improve processing precision and agility. This research paper aims to evaluate the detailed analysis of 3D image processing by using machine learning for man machine interaction. In this context, secondary analysis is to be done by taking information from different journals and articles. Google scholar, ProQuest databases are used to get relevant and proper journals related to topic.
Start page
2478
End page
2482
Language
English
OCDE Knowledge area
Informática y Ciencias de la Información Ingeniería de sistemas y comunicaciones
Scopus EID
2-s2.0-85135453607
ISBN
9781665437899
ISBN of the container
978-166543789-9
DOI of the container
10.1109/ICACITE53722.2022.9823699
Conference
2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022
Sources of information: Directorio de Producción Científica Scopus