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» Learning semantic object parts for object categorization
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WWW
2004
ACM
15 years 10 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...
CVPR
2010
IEEE
15 years 2 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 7 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 1 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 3 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