Deep learning for object detection in fine-art paintings

机译：美术绘画中对象检测深度学习

获取原文

页面导航

摘要
著录项
相似文献
相关主题

摘要

We propose deep learning and neural networks to automatically detect objects in digital pictures of fine-art paintings. This automatic annotation of digitized artwork provides innovation for content analysis, and therefore enhances the process of documenting and managing cultural heritage. Deep neural networks have outperformed all previous machine learning techniques in computer vision and achieve the highest accuracy in object detection. However, a very big amount of labeled training samples are required for such good performance. Typically, this big data is collected from everyday natural images, which is possible because millions are generated each day. Unfortunately there are not such big datasets of digitized fine-art paintings. In this contribution we present a set of strategies to overcome the lack of labeled training data, and hence make use of the promising deep learning in this application.

机译：我们提出了深入的学习和神经网络，以自动检测美术绘画的数码照片中的对象。这种自动注释数字化艺术品为内容分析提供了创新，从而增强了文档和管理文化遗产的过程。深度神经网络在计算机视觉中表现优于以前的所有机器学习技术，并在对象检测中实现最高精度。然而，这种良好的性能需要非常大量的标记训练样本。通常，从日常自然图像中收集该大数据，这是可能的，因为每天产生数百万。不幸的是，数字化美术绘画没有这样的大数据集。在这一贡献中，我们展示了一系列策略来克服缺乏标记的培训数据，因此利用本申请中有希望的深度学习。

著录项

来源
《Conference on Metrology for Archaeology and Cultural Heritage》|2018年|1 v.|共5页
会议地点
作者
Stanislav Smirnov; Alma Eguizabal;
展开▼
作者单位

展开▼
会议组织
原文格式 PDF
正文语种
中图分类文物考古;
关键词
Painting; Training; Machine learning; Object detection; Feature extraction; Support vector machines; Optimization;

机译：绘画;训练;机器学习;物体检测;特征提取;支持向量机;优化;

相似文献

外文文献
中文文献
专利

1. Hierarchical classification of fine-art paintings using deep neural networks [J] . Mohammad Reza Mohammadi, Fatemeh Rustaee Iran Journal of Computer Science . 2021,第1期

机译：深神经网络的美术绘画分类分类
2. An evaluation of deep learning based object detection strategies for threat object detection in baggage security imagery [J] . Dhiraj, Jain Deepak Kumar Pattern recognition letters . 2019,第APRa期

机译：基于深度学习的对象检测策略对行李安全图像中威胁对象检测的评估
3. Efficient Object Detection and Classification of Heat Emitting Objects from Infrared Images Based on Deep Learning [J] . Abeer D. Algarni Multimedia Tools and Applications . 2020,第19a20期

机译：基于深度学习的红外图像高效对象检测与散热物体的分类
4. Deep learning for object detection in fine-art paintings [C] . Stanislav Smirnov, Alma Eguizabal Conference on Metrology for Archaeology and Cultural Heritage . 2018

机译：深度学习用于美术绘画中的对象检测
5. Evaluation of Synthetic Training Data and Training-Data-Augmentation Techniques for Object Detection in Ground-Penetrating Radar Data using Deep-Learning Models [D] . Ruggiero, Jean. 2021

机译：使用深度学习模型评估用于地面穿透雷达数据的对象检测的综合训练数据和训练数据增强技术
6. A deep learning approach to automatic teeth detection and numbering based on object detection in dental periapical films [O] . Hu Chen, Kailai Zhang, Peijun Lyu, -1

机译：一种基于深度检测的根尖膜自动检测和编号的深度学习方法
7. EER-ASSL: Combining Rollback Learning and Deep Learning for Rapid Adaptive Object Detection [O] . 2020

机译：EER-ASSL：结合回滚学习和深度学习，快速自适应对象检测

Deep learning for object detection in fine-art paintings

摘要

著录项

相似文献

相关主题

期刊订阅