Partial annotations in active learning for semantic segmentation

IF 9.6 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY Automation in Construction Pub Date : 2024-10-22 DOI:10.1016/j.autcon.2024.105828
B.G. Pantoja-Rosero , A. Chassignet , A. Rezaie , M. Kozinski , R. Achanta , K. Beyer
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Abstract

Semantic segmentation with deep learning plays a crucial role in various fields, including civil engineering, particularly in tasks such as damage assessment and urban planning. This paper addresses the challenge of efficiently training deep learning models for semantic segmentation with a limited set of annotated data, thus reducing the burden of ground truth labeling. An active learning strategy is introduced, leveraging partial annotations informed by predictions and uncertainties from previously trained models. Unlike other active learning frameworks, this approach not only facilitates the annotation of highly uncertain image regions but also targets those with low uncertainty, which often lead to false positives and negatives. The results demonstrate that using partial annotations within an active learning framework significantly reduces manual annotation efforts and training time without compromising model performance. These findings have substantial implications for the efficiency and scalability of deep learning in civil engineering, paving the way for future research in active learning and semantic segmentation.
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语义分割主动学习中的部分注释
利用深度学习进行语义分割在包括土木工程在内的多个领域发挥着至关重要的作用,尤其是在损害评估和城市规划等任务中。本文探讨了如何利用有限的标注数据集高效地训练语义分割深度学习模型,从而减轻地面实况标注的负担。本文引入了一种主动学习策略,利用先前训练过的模型的预测和不确定性提供的部分注释。与其他主动学习框架不同的是,这种方法不仅有利于对高度不确定的图像区域进行标注,而且还能针对那些不确定性较低的区域进行标注,而不确定性较低的区域往往会导致假阳性和假阴性。研究结果表明,在主动学习框架内使用部分注释可显著减少人工注释工作量和训练时间,同时不会影响模型性能。这些发现对土木工程中深度学习的效率和可扩展性具有重大意义,为未来的主动学习和语义分割研究铺平了道路。
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来源期刊
Automation in Construction
Automation in Construction 工程技术-工程:土木
CiteScore
19.20
自引率
16.50%
发文量
563
审稿时长
8.5 months
期刊介绍: Automation in Construction is an international journal that focuses on publishing original research papers related to the use of Information Technologies in various aspects of the construction industry. The journal covers topics such as design, engineering, construction technologies, and the maintenance and management of constructed facilities. The scope of Automation in Construction is extensive and covers all stages of the construction life cycle. This includes initial planning and design, construction of the facility, operation and maintenance, as well as the eventual dismantling and recycling of buildings and engineering structures.
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