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» Learning the Relative Importance of Features in Image Data
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121
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DAGM
2005
Springer
15 years 9 months ago
Improving a Discriminative Approach to Object Recognition Using Image Patches
In this paper we extend a method that uses image patch histograms and discriminative training to recognize objects in cluttered scenes. The method generalizes and performs well for...
Thomas Deselaers, Daniel Keysers, Hermann Ney
189
Voted
SIGIR
2012
ACM
13 years 6 months ago
Content-based retrieval for heterogeneous domains: domain adaptation by relative aggregation points
We introduce the problem of domain adaptation for content-based retrieval and propose a domain adaptation method based on relative aggregation points (RAPs). Content-based retriev...
Makoto P. Kato, Hiroaki Ohshima, Katsumi Tanaka
ICCV
2007
IEEE
16 years 5 months ago
Limits of Learning-Based Superresolution Algorithms
Learning-based superresolution (SR) are popular SR techniques that use application dependent priors to infer the missing details in low resolution images (LRIs). However, their pe...
Zhouchen Lin, Junfeng He, Xiaoou Tang, Chi-Keung T...
140
Voted
APGV
2005
ACM
146views Visualization» more  APGV 2005»
15 years 9 months ago
A similarity-based approach to perceptual feature validation
Which object properties matter most in human perception may well vary according to sensory modality, an important consideration for the design of multimodal interfaces. In this st...
Theresa Cooke, Florian Steinke, Christian Wallrave...
134
Voted
ECCV
2004
Springer
16 years 5 months ago
Stretching Bayesian Learning in the Relevance Feedback of Image Retrieval
This paper is about the work on user relevance feedback in image retrieval. We take this problem as a standard two-class pattern classification problem aiming at refining the retri...
Ruofei Zhang, Zhongfei (Mark) Zhang