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Manifesting construction activity scenes via image captioning

机译:通过图像标题显示施工活动场景

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This study proposed an automated method for manifesting construction activity scenes by image captioning - an approach rooted in computer vision and natural language generation. A linguistic description schema for manifesting the scenes is developed initially and two unique dedicated image captioning datasets are created for method validation. A general model architecture of image captioning is then instituted by combining an encoder -decoder framework with deep neural networks, followed by three experimental tests involving the selection of model learning strategies and performance evaluation metrics. It is demonstrated the method's performance is comparable with that of state-of-the-art computer vision methods in general. The paper concludes with a discussion of the feasibility of the practical application of the proposed approach at the current technical level.
机译:本研究提出了一种通过图像标题表现出施工活动场景的自动化方法 - 一种植根于计算机视觉和自然语言生成的方法。最初开发了用于表现场景的语言描述架构,并且为方法验证创建了两个唯一的专用图像标题数据集。然后,通过将编码器-Decoder框架与深神经网络组合,然后三次实验测试来实现图像标题的一般模型架构,其次是涉及选择模型学习策略和性能评估度量的实验测试。据证明,该方法的性能与一般的最先进的计算机视觉方法相当。本文讨论了拟议方法在目前的技术水平的实际应用的可行性的讨论。

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