acrobat
发表于 2025-3-28 17:16:55
Applications of Deep Learning in Intelligent Construction,, and real-time supervision of construction sites with intelligent systems of controllability, data, and visualization. In particular, it is common to install many cameras in smart construction sites. These cameras only play the role of visualization, and further analysis is necessary to extract inf
Negligible
发表于 2025-3-28 21:47:24
Integrated SHM Systems: Damage Detection Through Unsupervised Learning and Data Fusion,esponse to this challenge falls within the framework of structural health monitoring (SHM), which pursues the automated diagnosis and prognosis of structures from continuously acquired sensor data. In the last years, particular attention has been devoted in the literature to ambient vibration-based
音乐学者
发表于 2025-3-29 01:56:25
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羽饰
发表于 2025-3-29 05:16:43
Vibration-Based Damage Feature for Long-Term Structural Health Monitoring Under Realistic Environmehese are sensitive to structural properties variations. The influence of environmental and operational variability on modal parameters sets limits to unsupervised learning strategies in real-world applications, especially for long-time series. The chapter shows an example of unsupervised learning da
露天历史剧
发表于 2025-3-29 10:20:51
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STING
发表于 2025-3-29 13:23:08
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Minuet
发表于 2025-3-29 16:55:45
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贫困
发表于 2025-3-29 19:49:42
Interpretable Machine Learning for Function Approximation in Structural Health Monitoring,, many resulting systems are opaque, making them neither interpretable nor trustworthy. Interpretable machine learning (IML) is an active new direction intended to match algorithm accuracy with transparency, enabling users to understand their systems. This chapter overviews existing IML work and phi
orthopedist
发表于 2025-3-30 02:27:20
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–DOX
发表于 2025-3-30 06:17:14
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