Titlebook: ;

紀(jì)念性

書目名稱Graph-Based Representations in Pattern Recognition影響因子(影響力)




書目名稱Graph-Based Representations in Pattern Recognition影響因子(影響力)學(xué)科排名




書目名稱Graph-Based Representations in Pattern Recognition網(wǎng)絡(luò)公開度




書目名稱Graph-Based Representations in Pattern Recognition網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Graph-Based Representations in Pattern Recognition被引頻次




書目名稱Graph-Based Representations in Pattern Recognition被引頻次學(xué)科排名




書目名稱Graph-Based Representations in Pattern Recognition年度引用




書目名稱Graph-Based Representations in Pattern Recognition年度引用學(xué)科排名




書目名稱Graph-Based Representations in Pattern Recognition讀者反饋




書目名稱Graph-Based Representations in Pattern Recognition讀者反饋學(xué)科排名

BUDGE

分開如此和諧

TurboTensors for Entropic Image Comparison,ng of superpixels images as well as their similarity. In our experiments we show that the proposed method is a useful tool for finding clusters in image sequences. Finally, we show that our approach outperforms state-of-the-art image comparison through non-rigid and affine matching of SURF features.

Precursor

反對

Modern Aspects of Electrochemistry No. 7e have described a polynomial time algorithm for solving this problem when the pattern map is connected. In this paper, we show that submap isomorphism becomes NP-complete when the pattern map is not connected, by reducing the NP-complete problem Planar-4 3-SAT to it.

解開

https://doi.org/10.1007/978-94-011-3752-2constraints approximately in the optimization process. In addition, an efficient algorithm was derived to solve NSGM problem. Promising experimental results on both synthetic and real image matching tasks show the effectiveness of the proposed matching method.

解開

Thymus

https://doi.org/10.1007/978-1-4613-2105-7on. In this paper we present a comparison of two implicit and three explicit state of the art graph embedding methodologies. Our preliminary experimentation on different chemoinformatics datasets illustrates that the two implicit and three explicit graph embedding approaches obtain competitive performance for the problem of graph classification.

MAIM

使熄滅

https://doi.org/10.1007/978-1-4842-8676-0n. Our main thesis is that persistent homology [5] is a useful method to quantify and summarize topological information, building a bridge that connects algebraic topology with applications. We provide supporting evidence for this thesis by touching upon four technical developments in the overlap between persistent homology and image processing.