Hypergraph-based image representation[A].Heidelberg:Springer Berlin,2005.A. Bretto and L. Gillibert. Hypergraph-based image representation. In International Workshop on Graph-Based Representations in Pattern Re
Wang, Deep high-resolution representation learning for human pose estimation, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019, pp. 5693–5703. Google Scholar [31] X. Wang, A. Gupta, Videos as space-time region graphs, in: Proceedings of the European ...
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Usage of extra information makes it available to estimate the face images of other variation types when face image of one variation type is known. The sparse-representation (SR)-based method [8], which aims to recover the sparse linear representation of any query sample with respect to a set...
without substantially increasing complexity. Through extensive experimentation across nine image datasets, we have demonstrated the effectiveness and superiority of the proposed algorithm. Comparative analyses, involving several state-of-the-art algorithms, were conducted, thereby elucidating the efficacy and ...
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This is accomplished via a context-sensitive image representation technique based on hypergraph model. First, each temporal image is modelled as a hypergraph that utilizes a set of hyperedges to capture the context-sensitive properties of pixels in the image. Second, the difference in the bi-...
This is accomplished via a context-sensitive image representation technique based on hypergraph model. First, each temporal image is modelled as a hypergraph that utilizes a set of hyperedges to capture the context-sensitive properties of pixels in the image. Second, the difference in the bi-...
image restorationsalt-and-pepper noise removalhyperedgesimage neighborhood hypergraph parameterINHG parameterAn algorithm is designed for the hypergraph (HG) representation of an image, subsequent detection of Salt and Pepper (SP) noise in the image and finally the restoration of the image from this ...
sparse representationquery by multiple examplesranking algorithmContent-based image retrieval (CBIR) always suffers from the so-called semantic gap. Query-By-Multiple-Examples (QBME) is introduced to bridge it and applied in a lot of CBIR systems. However, current QBME methods usually query with ...