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» Pruning Training Sets for Learning of Object Categories
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CVPR
2010
IEEE
14 years 5 months ago
Online-Batch Strongly Convex Multi Kernel Learning
Several object categorization algorithms use kernel methods over multiple cues, as they offer a principled approach to combine multiple cues, and to obtain state-of-theart perform...
Francesco Orabona, Jie Luo, Barbara Caputo
ICML
2005
IEEE
14 years 9 months ago
Using additive expert ensembles to cope with concept drift
We consider online learning where the target concept can change over time. Previous work on expert prediction algorithms has bounded the worst-case performance on any subsequence ...
Jeremy Z. Kolter, Marcus A. Maloof
SAMT
2007
Springer
95views Multimedia» more  SAMT 2007»
14 years 3 months ago
A Study of Vocabularies for Image Annotation
Abstract. In order to evaluate image annotation and object categorisation algorithms, ground truth in the form of a set of images correctly annotated with text describing each imag...
Allan Hanbury
AMR
2007
Springer
140views Multimedia» more  AMR 2007»
14 years 3 months ago
Learning Distance Functions for Automatic Annotation of Images
This paper gives an overview of recent approaches towards image representation and image similarity computation for content-based image retrieval and automatic image annotation (ca...
Josip Krapac, Frédéric Jurie
WWW
2004
ACM
14 years 9 months ago
Dynamic assembly of learning objects
This paper describes one solution to the problem of how to select sequence, and link Web resources into a coherent, focused organization for instruction that addresses a user'...
Robert G. Farrell, Soyini D. Liburd, John C. Thoma...