Titlebook: Image Analysis and Recognition; Third International Aurélio Campilho,Mohamed Kamel Conference proceedings 2006 Springer-Verlag Berlin Heid

根深蒂固

书目名称Image Analysis and Recognition影响因子(影响力)




书目名称Image Analysis and Recognition影响因子(影响力)学科排名




书目名称Image Analysis and Recognition网络公开度




书目名称Image Analysis and Recognition网络公开度学科排名




书目名称Image Analysis and Recognition被引频次




书目名称Image Analysis and Recognition被引频次学科排名




书目名称Image Analysis and Recognition年度引用




书目名称Image Analysis and Recognition年度引用学科排名




书目名称Image Analysis and Recognition读者反馈




书目名称Image Analysis and Recognition读者反馈学科排名

斜坡

送秋波

Alternative Approaches and Algorithms for Classificatione several advantages over the previous ones via the introduction of a new concept, Centers of Masses for classes, and new cost functions which enforce clustering of different classes more explicitly compared to the previous approaches.

gregarious

forbid

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/i/image/461403.jpg

手术刀

Using Local Integral Invariants for Object Recognition in Complex ScenesIntegral invariants capture the local structure of the neighborhood around the points where they are computed. This makes them very well suited for constructing highly-discriminative local descriptors. The features are by definition invariant to Euclidean motion. We show how to extend the local feat

Instantaneous

CLAN

Object Categorization Using Kernels Combining Graphs and Histograms of Gradients shape or appearance. In this paper, we aim at performing object recognition by mixing kernels obtained from different cues. Our method is based on two complementary descriptions of an object. First, we describe its shape thanks to labeled graphs. This graph is obtained from morphological skeleton,

Graphite

Alternative Approaches and Algorithms for Classificatione several advantages over the previous ones via the introduction of a new concept, Centers of Masses for classes, and new cost functions which enforce clustering of different classes more explicitly compared to the previous approaches.

Chameleon

A Pool of Classifiers by SLP: A Multi-class Caseial training of the perceptrons, one may obtain a pool of different classification algorithms. Means to improve training speed and reduce generalization error are studied. Training dynamics is illustrated by solving artificial multi-class pattern recognition task and important real world problem: de