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» Learning the Relative Importance of Features in Image Data
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MM
2009
ACM
277views Multimedia» more  MM 2009»
14 years 3 months ago
Inferring semantic concepts from community-contributed images and noisy tags
In this paper, we exploit the problem of inferring images’ semantic concepts from community-contributed images and their associated noisy tags. To infer the concepts more accura...
Jinhui Tang, Shuicheng Yan, Richang Hong, Guo-Jun ...
AICT
2006
IEEE
14 years 2 months ago
Privacy and data protection in technology-enhanced professional learning
Privacy provision and data protection are basic requirements for professional learning, especially when personalized systems are used that adapt to sensitive learner personal data...
Tomaz Klobucar
SAC
2006
ACM
14 years 2 months ago
The impact of sample reduction on PCA-based feature extraction for supervised learning
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
3DIM
2003
IEEE
14 years 9 days ago
Surflet-Pair-Relation Histograms: A Statistical 3D-Shape Representation for Rapid Classification
A statistical representation of three-dimensional shapes is introduced, based on a novel four-dimensional feature. The feature parameterizes the intrinsic geometrical relation of ...
Eric Wahl, Ulrich Hillenbrand, Gerd Hirzinger
ECCV
2010
Springer
14 years 1 months ago
On Parameter Learning in CRF-based Approaches to Object Class Image Segmentation
Recent progress in per-pixel object class labeling of natural images can be attributed to the use of multiple types of image features and sound statistical learning approaches. Wit...