BROTH
发表于 2025-3-23 12:47:31
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jaundiced
发表于 2025-3-23 17:53:33
Sports Classification Using Cross-Ratio Histogramse proposed approach uses invariant nature of a cross-ratio under projective transformation to develop a robust classifier. For a given image, cross-ratios are computed for the points obtained from the intersection of lines detected using Hough transform. These cross-ratios are represented by a histo
Esophagitis
发表于 2025-3-23 20:41:45
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Demulcent
发表于 2025-3-23 23:00:32
Efficient Graph Cuts for Multiclass Interactive Image Segmentation segmentation is foreground/background segmentation based on user specified brush labellings. The problem can be formulated within the binary Markov Random Field (MRF) framework which can be solved efficiently via graph cut . However, no attempt has yet been made to handle segmentation of multipl
curettage
发表于 2025-3-24 04:47:23
Feature Subset Selection for Multi-class SVM Based Image Classificationselection criterion for the multi-class SVMs. By minimizing this criterion, the scale factors assigned to each feature in a kernel function are optimized to identify the important features. This minimization problem can be efficiently solved by gradient-based search techniques, even if hundreds of f
无能性
发表于 2025-3-24 08:53:10
Evaluating Multi-class Multiple-Instance Learning for Image Categorization. Typical current MIL schemes rely on binary one-versus-all classification, even for inherently multi-class problems. There are a few drawbacks with binary MIL when applied to a multi-class classification problem. This paper describes Multi-class Multiple-Instance Learning (McMIL) to image categoriz
MAIZE
发表于 2025-3-24 12:12:19
TransforMesh : A Topology-Adaptive Mesh-Based Approach to Surface Evolutionmetrization, while allowing for an accurate surface representation, suffers from the inherent problems of not being able to reliably deal with self-intersections and topology changes. As a consequence, an important number of methods choose implicit representations of surfaces, e.g. level set methods
PALL
发表于 2025-3-24 17:30:28
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叫喊
发表于 2025-3-24 19:43:47
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MENT
发表于 2025-3-25 01:03:15
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