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» Explanation-Based Learning for Image Understanding
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DAS
2010
Springer
13 years 11 months ago
Memory-based recognition of camera-captured characters
This paper addresses how to quickly recognize a character pattern using a lot of case examples without learning. Here without learning means just finding the most similar example...
Masakazu Iwamura, Tomohiko Tsuji, Koichi Kise
KDD
2009
ACM
257views Data Mining» more  KDD 2009»
14 years 2 months ago
Argo: intelligent advertising by mining a user's interest from his photo collections
In this paper, we introduce a system named Argo which provides intelligent advertising made possible from users’ photo collections. Based on the intuition that user-generated ph...
Xin-Jing Wang, Mo Yu, Lei Zhang, Rui Cai, Wei-Ying...
IJCNN
2006
IEEE
14 years 1 months ago
A Comparison between Recursive Neural Networks and Graph Neural Networks
— Recursive Neural Networks (RNNs) and Graph Neural Networks (GNNs) are two connectionist models that can directly process graphs. RNNs and GNNs exploit a similar processing fram...
Vincenzo Di Massa, Gabriele Monfardini, Lorenzo Sa...
EMMCVPR
2007
Springer
14 years 1 months ago
Bottom-Up Recognition and Parsing of the Human Body
Recognizing humans, estimating their pose and segmenting their body parts are key to high-level image understanding. Because humans are highly articulated, the range of deformation...
Praveen Srinivasan, Jianbo Shi
CVPR
2012
IEEE
11 years 10 months ago
A learning-based framework for depth ordering
Depth ordering is instrumental for understanding the 3D geometry of an image. We as humans are surprisingly good ordering even with abstract 2D line drawings. In this paper we pro...
Zhaoyin Jia, Andrew C. Gallagher, Yao-Jen Chang, T...