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» Latent Hierarchical Structural Learning for Object Detection
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CVPR
2009
IEEE
15 years 2 months ago
HOP: Hierarchical Object Parsing
In this paper we consider the problem of object parsing, namely detecting an object and its components by composing them from image observations. Apart from object localization, ...
Iasonas Kokkinos, Alan L. Yuille
APSCC
2008
IEEE
14 years 2 months ago
Adaptive Learning Sequencing for Course Customization: A Web Service Approach
— We discuss a learning model that enables the creation of optimal learning strategies that suit learners’ needs. A customized learning content is delivered to learners as mana...
Ivan Madjarov, Abdelkader Bétari
ICASSP
2009
IEEE
13 years 5 months ago
Probabilistic matrix tri-factorization
Nonnegative matrix tri-factorization (NMTF) is a 3-factor decomposition of a nonnegative data matrix, X USV , where factor matrices, U, S, and V , are restricted to be nonnegativ...
Jiho Yoo, Seungjin Choi
AAAI
2012
11 years 10 months ago
Transfer Learning with Graph Co-Regularization
Transfer learning proves to be effective for leveraging labeled data in the source domain to build an accurate classifier in the target domain. The basic assumption behind transf...
Mingsheng Long, Jianmin Wang 0001, Guiguang Ding, ...
ICCV
2005
IEEE
14 years 9 months ago
A Hierarchical Field Framework for Unified Context-Based Classification
We present a two-layer hierarchical formulation to exploit different levels of contextual information in images for robust classification. Each layer is modeled as a conditional f...
Sanjiv Kumar, Martial Hebert