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» Pruning Training Sets for Learning of Object Categories
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CVPR
2008
IEEE
14 years 9 months ago
Decomposition, discovery and detection of visual categories using topic models
We present a novel method for the discovery and detection of visual object categories based on decompositions using topic models. The approach is capable of learning a compact and...
Mario Fritz, Bernt Schiele
ICML
2010
IEEE
13 years 8 months ago
Cognitive Models of Test-Item Effects in Human Category Learning
Imagine two identical people receive exactly the same training on how to classify certain objects. Perhaps surprisingly, we show that one can then manipulate them into classifying...
Xiaojin Zhu, Bryan R. Gibson, Kwang-Sung Jun, Timo...
CVPR
2007
IEEE
14 years 2 months ago
Matrix-Structural Learning (MSL) of Cascaded Classifier from Enormous Training Set
Aiming at the problem when both positive and negative training set are enormous, this paper proposes a novel Matrix-Structural Learning (MSL) method, as an extension to Viola and ...
Shengye Yan, Shiguang Shan, Xilin Chen, Wen Gao, J...
CVPR
2005
IEEE
14 years 9 months ago
A Bayesian Hierarchical Model for Learning Natural Scene Categories
We propose a novel approach to learn and recognize natural scene categories. Unlike previous work [9, 17], it does not require experts to annotate the training set. We represent t...
Fei-Fei Li 0002, Pietro Perona, California Institu...
CVPR
2007
IEEE
14 years 9 months ago
Beyond Local Appearance: Category Recognition from Pairwise Interactions of Simple Features
We present a discriminative shape-based algorithm for object category localization and recognition. Our method learns object models in a weakly-supervised fashion, without requiri...
Marius Leordeanu, Martial Hebert, Rahul Sukthankar