我们该如何处理?与(半)自动检测到的网站和功能有关的挑战。说明

Q2 Arts and Humanities
Niko Anttiroiko
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引用次数: 1

摘要

机器学习和计算机视觉技术的最新进展使越来越多的考古学家和考古机构(包括芬兰的考古机构)能够进行(半)自动特征检测。这些技术提高了我们以高效方式探测和收集广袤地区考古文化遗产信息的能力。然而,这些方法的广泛应用也给考古文化遗产管理带来了巨大挑战,尤其是对 17-20 世纪几乎无处不在的某些类型的考古遗迹。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
What Should We Do With These? Challenges related to (semi-)automatically detected sites and features. A note
Recent advances in machine learning and computer vision techniques have brought (semi-)automatic feature detection within reach of an increasing number of archaeologists and archaeological institutions, including those in Finland. These techniques improve our ability to detect and gather information on archaeological cultural heritage over vast areas in a highly efficient manner. However, the widespread adoption of such methods can also pose significant challenges for archaeological cultural heritage management, especially in relation to certain types of near-ubiquitous archaeological remains from the 17th-20th centuries.
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来源期刊
Internet Archaeology
Internet Archaeology Arts and Humanities-Archeology (arts and humanities)
CiteScore
1.10
自引率
0.00%
发文量
9
审稿时长
16 weeks
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