ARTDET：用于自动检测架上绘画艺术品劣化的机器学习软件

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX Pub Date : 2024-10-05 DOI:10.1016/j.softx.2024.101917

Francisco M. Garcia-Moreno , Jesús Cortés Alcaraz , José Manuel del Castillo de la Fuente , Luis Rodrigo Rodríguez-Simón , María Visitación Hurtado-Torres

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引用次数: 0

摘要

随着人们对文化遗产数字化保护的兴趣与日俱增，ARTDET 应运而生，这是一款用于自动检测架上绘画损毁情况的机器学习软件。该网络应用程序使用预先训练好的掩膜 R-CNN 模型来检测绘画层（LPL）和灰泥修复造成的漆面缺失（导致可见支撑板的缺失区域）。ARTDET 利用了修复专家标注的高分辨率图像。该软件对 LPL 和灰泥的召回率达到 80.4%，对检测到的损坏的置信度达到 99%。ARTDET 可作为开放存取资源，帮助保护人员和研究人员保护珍贵的艺术品。

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ARTDET: Machine learning software for automated detection of art deterioration in easel paintings

The increasing interest in digital preservation of cultural heritage has led to ARTDET, a machine learning software for automated detection of deterioration in easel paintings. This web application uses a pre-trained Mask R-CNN model to detect Lacune (areas of missing paint, resulting in visible support panel) from the loss of the Painting Layer (LPL) and stucco repairs. ARTDET leverages high-resolution images annotated by expert restorers. The software achieved 80.4 % recall for LPL and stucco, with a 99 % confidence score in detected damages. Available as open access resource, ARTDET aids conservators and researchers in preserving invaluable artworks.

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来源期刊

SoftwareX COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

5.50

自引率

2.90%

发文量

184

审稿时长

9 weeks

期刊介绍： SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.