Automated Ai-Driven Feature Extraction for Archaeological Site Detection in the North Peninsular Malaysia, Bujang Valley
Shairatul Akma Roslan, Rahinah Ibrahim, Normaisharah Mamat · 2025
Abstract—The comprehensive study begins by examining the current landscape of archaeological site detection, focusing on the integration of advanced technologies; and Artificial Intelligence-Remote Sensing (AI-RS) driven feature extraction. Identifying a critical issue related to the precision of archaeological site identification and the lack of interpretative frameworks poses significant challenges to archaeologists and technology makers. This research departs from traditional approaches by bridging the gap between automated detection and qualitative interpretation, specifically targeting the prominent archaeological heritage complex of the Bujang Valley in North Peninsular Malaysia. Through a case study approach, incorporating interviews and field observations, this study systematically investigates the application of AI-RS-driven methodologies, aiming to develop a more effective and innovative way to enhance archaeological feature detection and interpretation. This comprehensive study is improving the preliminary study’s result from “Artificial Intelligence-Remote Sensing for Rapid Mapping of Potential Archaeological Features using Image Classification: Bag of Visual Words-based”. The expected output will contribute to the field by providing new insights into identifying potential hidden archaeological areas using automated detection AI-RS. By synthesizing technical robustness with contextual understanding, the research fosters a more comprehensive understanding of archaeological environments, advancing both technological development and archaeological interpretation practices. Keywords: Artificial Intelligence, Remote Sensing; Feature Extraction; Archaeology; Bujang Valley