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» Learning the Relative Importance of Features in Image Data
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166
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BMCBI
2010
171views more  BMCBI 2010»
15 years 3 months ago
PyMix - The Python mixture package - a tool for clustering of heterogeneous biological data
Background: Cluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers...
Benjamin Georgi, Ivan Gesteira Costa, Alexander Sc...
148
Voted
MM
2006
ACM
203views Multimedia» more  MM 2006»
15 years 9 months ago
Learning image manifolds by semantic subspace projection
In many image retrieval applications, the mapping between highlevel semantic concept and low-level features is obtained through a learning process. Traditional approaches often as...
Jie Yu, Qi Tian
134
Voted
ECCV
2004
Springer
15 years 9 months ago
Statistical Learning of Evaluation Function for ASM/AAM Image Alignment
Alignment between the input and target objects has great impact on the performance of image analysis and recognition system, such as those for medical image and face recognition. A...
Xiangsheng Huang, Stan Z. Li, Yangsheng Wang
144
Voted
ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
15 years 1 months ago
Multi-label Feature Selection for Graph Classification
Nowadays, the classification of graph data has become an important and active research topic in the last decade, which has a wide variety of real world applications, e.g. drug acti...
Xiangnan Kong, Philip S. Yu
134
Voted
PR
2010
147views more  PR 2010»
15 years 2 months ago
Minimum classification error learning for sequential data in the wavelet domain
Wavelet analysis has found widespread use in signal processing and many classification tasks. Nevertheless, its use in dynamic pattern recognition have been much more restricted ...
D. Tomassi, Diego H. Milone, L. Forzani