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Titlebook: Energy Minimization Methods in Computer Vision and Pattern Recognition; 4th International Wo Anand Rangarajan,Mário Figueiredo,Josiane Zeru

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21#
發(fā)表于 2025-3-25 06:13:41 | 只看該作者
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發(fā)表于 2025-3-25 14:32:06 | 只看該作者
Local PCA for Strip Line Detection and Thinning rival penalized competitive learning (RPCL) based local principal component analysis (PCA). Due to its model selection and noise resistance ability, the technique is shown to outperform conventional Hough transform and thinning algorithms via a number of simulations.
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發(fā)表于 2025-3-25 17:18:56 | 只看該作者
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發(fā)表于 2025-3-25 23:27:46 | 只看該作者
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/e/image/310346.jpg
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發(fā)表于 2025-3-26 03:42:45 | 只看該作者
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發(fā)表于 2025-3-26 13:24:23 | 只看該作者
Wenn es vermeintlich am K?nnen fehlts of the solution. The ROC curve obtained shows better performance than the baseline model. Finally, color gradient is included. Thanks to Bethe tree approximation, we obtain a simple analytical expression for the coefficients of the associated maximum entropy model. Performance, compared with previous model is once more improved.
30#
發(fā)表于 2025-3-26 16:54:36 | 只看該作者
Stochastic Search for Optimal Linear Representations of Images on Spaces with Orthogonality Constrairy of the underlying manifolds to find optimal linear representations for specified tasks. We illustrate the effectiveness of algorithms by finding optimal subspaces and sparse filters both in the context of image-based object recognition.
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