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» Learning semantic object parts for object categorization
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WWW
2004
ACM
16 years 6 days 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...
CVPR
2010
IEEE
15 years 4 months ago
An Online Approach: Learning-Semantic-Scene-by-Tracking and Tracking-by-Learning-Semantic-Scene
Learning the knowledge of scene structure and tracking a large number of targets are both active topics of computer vision in recent years, which plays a crucial role in surveilla...
Xuan Song, Xiaowei Shao, Huijing Zhao, Jinshi Cui,...
BMVC
2010
14 years 9 months ago
Insect Species Recognition using Sparse Representation
Insect species recognition is a typical application of image categorization and object recognition. Unlike generic image categorization datasets (such as the Caltech 101 dataset) ...
An Lu, Xin Hou, Chen Lin, Cheng-Lin Liu
CVPR
2011
IEEE
14 years 3 months ago
Kernelized Structural SVM Learning for Supervised Object Segmentation
Object segmentation needs to be driven by top-down knowledge to produce semantically meaningful results. In this paper, we propose a supervised segmentation approach that tightly ...
Luca Bertelli, Tianli Yu, Diem Vu, Salih Gokturk
CVPR
2005
IEEE
15 years 5 months ago
A Discriminative Framework for Modelling Object Classes
Here we explore a discriminative learning method on underlying generative models for the purpose of discriminating between object categories. Visual recognition algorithms learn m...
Alex Holub, Pietro Perona