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» Latent Hierarchical Structural Learning for Object Detection
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TSMC
2008
162views more  TSMC 2008»
13 years 7 months ago
Codevelopmental Learning Between Human and Humanoid Robot Using a Dynamic Neural-Network Model
The paper examines characteristics of interactive learning between human tutors and a robot having a dynamic neural network model which is inspired by human parietal cortex functio...
Jun Tani, Ryunosuke Nishimoto, Jun Namikawa, Masat...
ECCV
2010
Springer
14 years 19 days ago
Weakly Supervised Shape Based Object Detection with Particle Filter
Abstract. We describe an efficient approach to construct shape models composed of contour parts with partially-supervised learning. The proposed approach can easily transfer parts ...
NIPS
2004
13 years 9 months ago
Contextual Models for Object Detection Using Boosted Random Fields
We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which use boos...
Antonio Torralba, Kevin P. Murphy, William T. Free...
PAMI
2000
113views more  PAMI 2000»
13 years 7 months ago
Hierarchical Discriminant Regression
This paper presents a new technique which incrementally builds a hierarchical discriminant regression (IHDR) tree for generation of motion based robot reactions. The robot learned...
Wey-Shiuan Hwang, Juyang Weng
TCSV
2010
13 years 2 months ago
A Hierarchical Bayesian Generation Framework for Vacant Parking Space Detection
In this paper, from the viewpoint of scene understanding, a 3-layer Bayesian hierarchical framework (BHF) is proposed for robust vacant parking space detection. In practice, the ch...
Chingchun Huang, Sheng-Jyh Wang