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A Computer Vision Framework for Automatic Description of Indian Monuments

机译:自动描述印度古迹的计算机视觉框架

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Monument recognition and description has emerged as a promising area of research. For any given image of a monument a question arises that up to what extend can a computer model describe the monument from that image?The main objective of the paper is to propose a framework which is capable of identifying multiple attributes from a single image of a monument. Four different attributes i.e. the class of the monument, the style of the architecture, the time period in which the monument was constructed and the type of the monument are taken into consideration. The paper proposes a framework that relies on Deep Convolutional Neural Networks (DCNN) for describing the monument in terms of the aforementioned attributes. The experiments have been performed on a dataset comprising of 6102 images of 117 Indian monuments. The model was able to achieve an accuracy greater than 80% for all the different set of experimentations. The results clearly indicate the usefulness of the framework.
机译:纪念碑的识别和描述已成为有前途的研究领域。对于任何给定的纪念物图像,都会出现一个问题,即计算机模型可以从该图像中描述纪念物的范围是多少?本文的主要目的是提出一种框架,该框架能够从单个图像中识别出多个属性。纪念碑。考虑了四个不同的属性,即纪念碑的类别,建筑风格,建造纪念碑的时间段和纪念碑的类型。本文提出了一个框架,该框架依赖于深度卷积神经网络(DCNN)来根据上述属性描述纪念碑。实验是在包含117个印度古迹的6102个图像的数据集上进行的。对于所有不同的实验,该模型均能够达到80%以上的精度。结果清楚地表明了该框架的有用性。

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