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All Journal Sinergi
Ade Purwanto
National Research and Innovation Agency (BRIN)
Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Journal : Sinergi

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Image Segmentation in Aerial Imagery: A Review Ade Purwanto; Dewi Habsari Budiarti; Fithri Nur Purnamastuti; Irfansyah Yudhi Tanasa; Yomi Guno; Aris Surya Yunata; Mukti Wibowo; Asyaraf Hidayat; Dede Dirgahayu
SINERGI Vol 27, No 3 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.3.006

Abstract

The problem of distinguishing objects has plagued researchers for many years because of low accuracy compared to human eyes’ capability. In the last decade, the use of Machine Learning in aerial imagery data processing has multiplied, with the technology behind it has also developed exponentially. One of those technologies is image-based object identification, which relies heavily upon data computation. To reduce the computational load, various data segmentation algorithm was developed. This study is focused on reviewing the various image segmentation technology in aerial imagery for image recognition. Literature from as far as 1981 from various journals and conferences worldwide was reviewed. This review examines specific research questions to analyze image segmentation research over time and the challenges researchers face with each method. Machine Learning has gained popularity among segmentation methods. However, Deep Learning has been aggressively put an essential role in it by overcoming many of its weaknesses. The advanced algorithm used in Deep Learning to process the segmentation may drive more efficient and accurate data processing. 
Co-Authors Aris Surya Yunata Asyaraf Hidayat Dede Dirgahayu Dewi Habsari Budiarti Fithri Nur Purnamastuti Irfansyah Yudhi Tanasa Mukti Wibowo Yomi Guno