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High-performance content-based image retrieval using DFS strategy

机译:使用DFS策略的基于内容的高性能图像检索

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Image data is becoming more and more popular due to the prevalence of image capture devices. How to retrieve the images effectively and efficiently from a large number of images has been a challenging issue in recent years. To deal with such issue, the major purpose of this paper is to propose a concept- and content-aware image retrieval approach using Depth-First Search (DFS) strategy to conduct effective and efficient image semantic retrieval. For effectiveness and efficiency, since the search space is reduced into specific subspaces, the retrieval cost is decreased and the retrieval quality is increased. For semantic retrieval, our proposed method can detect the potential concepts to satisfy the user's semantic need. In the experimental result, it reveals that our proposed approach is more effective and efficient than traditional ones using Breadth-First-Search (BFS) strategy.
机译:由于图像捕获设备的普及,图像数据变得越来越流行。近年来,如何有效地从大量图像中检索图像一直是一个具有挑战性的问题。为了解决这个问题,本文的主要目的是提出一种使用深度优先搜索(DFS)策略进行概念和内容感知的图像检索方法,以进行有效而高效的图像语义检索。为了提高效率和效率,由于将搜索空间缩小为特定的子空间,因此降低了检索成本并提高了检索质量。对于语义检索,我们提出的方法可以检测潜在的概念以满足用户的语义需求。在实验结果中,它表明我们提出的方法比使用广度优先搜索(BFS)策略的传统方法更加有效。

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