by Ranyah Taha, Fuad Musleh and Abdel Rahman Musleh
Journal of Engineering Research and Sciences, Volume 4, Issue 6, Page # 1-8, 2025; DOI: 10.55708/js0406001
Abstract: Wildfires are a growing global concern, causing widespread environmental, economic, and health impacts. In the USA, fire incidents have become more frequent and intense due to factors such as climate change, prolonged droughts, and human activities. Machine learning plays a vital role in predicting and classifying fires by analyzing vast satellite and environmental datasets with… Read More

(This article belongs to the Special Issue on SP6 (Special Issue on Computing, Engineering and Sciences (SI-CES 2024-25)) and the Section Remote Sensing (RMS))

by Yi Liu, Wendy Wang, Haibo Wang and Bahram Alidaee
Journal of Engineering Research and Sciences, Volume 2, Issue 12, Page # 23-33, 2023; DOI: 10.55708/js0212004
Abstract: Information extracted from remote sensing data can be applied to monitor the business and natural environments of a geographic area. Although a wide range of classical machine learning techniques have been utilized to obtain such information, their performance differs greatly in classification accuracy. In this study, we aim to examine whether quantum-enhanced machine learning can… Read More

(This article belongs to the Section Remote Sensing (RMS))