１．カバーシート（カバーシートフォーム）
40字×40行程度以内で以下の順に記載する。

a. 論文種類、分野
科学系分野

b. 論文題名(和文、英文)
Tumulus Distribution Prediction in the Iwase Senzuka Tumulus Cluster with Topographic Maps

c. 著者名(和文、英文)
Mengbo You (1) , Kouichi Konno (1), Atsushi Noguchi (2), Ryosuke Nakamura (3), Yuichi Takata (4)

d. 著者所属(和文、英文)
1) Iwate University
2) Komatsu University Research Center for Next Generation Archaeological Studies 
3) The National Institute of Advanced Industrial Science and Technology (AIST) 
4) Nara National Institute for Cultural Properties

e. 著者e-mail
ymb@iwate-u.ac.jp,konno21@iwate-u.ac.jp

f. 連絡担当者の氏名、住所、所属、電話、Fax、e-mail
氏名：游 梦博
住所：〒020-8551 岩手県盛岡市上田4-3-5
所属：岩手大学理工学部
			  システム創成工学科 知能・メディア情報コース
　　　　総合科学研究科　理工学専攻 デザイン・メディア工学コース
　　　　工学研究科　デザイン・メディア工学専攻
電話： 019-621-6470
E-mail：ymb@iwate-u.ac.jp

g. 論文概要(和文400字程度、英文100ワード程度)
Conducting comprehensive excavations in the extensive areas surrounding ancient tumulus clusters can reveal the locations of undiscovered tumuli. However, such endeavors demand significant manpower, resources, and time. By preemptively estimating the locations of these tumuli, we can avoid unnecessary excavations and improve efficiency. This study aims to examine the correlation between the distribution of ancient tumuli and topographical features. Leveraging this correlation, our goal is to forecast the likelihood of encountering ancient tumuli in various unexplored areas around the Iwase Senzuka tumulus cluster. This paper proposes a novel method to analyze the topographic point cloud data. The method involves superimposing archaeological markings onto the derived topographic map for annotation, cropping out patches and combining them to predict the likelihood of tumulus presence. The generated 2D distribution heatmaps are integrated and mapped to a color-coded point cloud for simultaneous observation of the important feature distribution identified by the deep learning network and examination of the 3D topography.

h. キーワード(和文5個程度、英文5個程度)
tumuli distribution, location prediction, topographic features, image identification, 3D visulization