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» Incremental Multiple Kernel Learning for object recognition
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ICCV
2005
IEEE
14 years 9 months ago
The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features
Discriminative learning is challenging when examples are sets of features, and the sets vary in cardinality and lack any sort of meaningful ordering. Kernel-based classification m...
Kristen Grauman, Trevor Darrell
ACCV
2010
Springer
13 years 2 months ago
Randomised Manifold Forests for Principal Angle-Based Face Recognition
Abstract. In set-based face recognition, each set of face images is often represented as a linear/nonlinear manifold and the Principal Angles (PA) or Kernel PAs are exploited to me...
Ujwal D. Bonde, Tae-Kyun Kim, K. R. Ramakrishnan
ICDAR
2009
IEEE
14 years 2 months ago
Learning and Adaptation for Improving Handwritten Character Recognizers
Writer independent handwriting recognition systems are limited in their accuracy, primarily due the large variations in writing styles of most characters. Samples from a single ch...
Naveen Chandra Tewari, Anoop M. Namboodiri
ICML
2010
IEEE
13 years 8 months ago
COFFIN: A Computational Framework for Linear SVMs
In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
Sören Sonnenburg, Vojtech Franc
PSIVT
2009
Springer
400views Multimedia» more  PSIVT 2009»
14 years 2 months ago
Local Image Descriptors Using Supervised Kernel ICA
PCA-SIFT is an extension to SIFT which aims to reduce SIFT’s high dimensionality (128 dimensions) by applying PCA to the gradient image patches. However PCA is not a discriminati...
Masaki Yamazaki, Sidney Fels