EconPapers    
Economics at your fingertips  
 

Object-based Classification of Natural Scenes Using Machine Learning Methods

Mohammed Saaduldeen Jasim ()

Technium, 2023, vol. 6, issue 1, 1-22

Abstract: The replication of human intellectual processes by machines, particularly computer systems, is known as artificial intelligence (AI). AI is an intelligent tool that is utilized across sectors to improve decision making, increase productivity, and eliminate repetitive tasks. Machine learning (ML) is a key component of AI since it includes understanding and developing ways that can learn or improve performance on tasks. For the last decade, ML has been applied in computer vision (CV) applications. In computer vision, systems and computers extract meaningful data from digital videos, photos, and other visual sources and use that information to conduct actions or make suggestions. In this work, we have solved the image segmentation problem for the natural images to segment out water, land, and sky. Instead of applying image segmentation directly to the images, images are pre-processed, and statistical and textural features are then passed through a neural network for the pixel-wise semantic segmentation of the images. We chose the 5X5 window over the pixel-by-pixel technique since it requires less resources and time for training and testing.

Date: 2023
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://techniumscience.com/index.php/technium/article/view/8286/3082 (application/pdf)
https://techniumscience.com/index.php/technium/article/view/8286 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:tec:techni:v:6:y:2023:i:1:p:1-22

DOI: 10.47577/technium.v6i.8286

Access Statistics for this article

Technium is currently edited by Scurtu Ionut Cristian

More articles in Technium from Technium Science
Bibliographic data for series maintained by Ana Maria Golita ().

 
Page updated 2025-03-20
Handle: RePEc:tec:techni:v:6:y:2023:i:1:p:1-22