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BVAI
2007
Springer
14 years 1 months ago
Neural Object Recognition by Hierarchical Learning and Extraction of Essential Shapes
We present a hierarchical system for object recognition that models neural mechanisms of visual processing identified in the mammalian ventral stream. The system is composed of ne...
Daniel Oberhoff, Marina Kolesnik
CVPR
2011
IEEE
13 years 3 months ago
On Deep Generative Models with Applications to Recognition
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Marc', Aurelio Ranzato, Joshua Susskind, Volodymyr...
ICML
2010
IEEE
13 years 8 months ago
Cognitive Models of Test-Item Effects in Human Category Learning
Imagine two identical people receive exactly the same training on how to classify certain objects. Perhaps surprisingly, we show that one can then manipulate them into classifying...
Xiaojin Zhu, Bryan R. Gibson, Kwang-Sung Jun, Timo...
CVPR
2006
IEEE
14 years 9 months ago
Improving Recognition of Novel Input with Similarity
Many sources of information relevant to computer vision and machine learning tasks are often underused. One example is the similarity between the elements from a novel source, suc...
Jerod J. Weinman, Erik G. Learned-Miller
CVPR
2008
IEEE
14 years 9 months ago
Semi-supervised learning of multi-factor models for face de-identification
With the emergence of new applications centered around the sharing of image data, questions concerning the protection of the privacy of people visible in the scene arise. Recently...
Ralph Gross, Latanya Sweeney, Fernando De la Torre...