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» Domain Adaptation for Object Recognition: An Unsupervised Ap...
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JMLR
2012
13 years 3 months ago
On Nonparametric Guidance for Learning Autoencoder Representations
Unsupervised discovery of latent representations, in addition to being useful for density modeling, visualisation and exploratory data analysis, is also increasingly important for...
Jasper Snoek, Ryan Prescott Adams, Hugo Larochelle
UIST
2004
ACM
15 years 6 months ago
Hierarchical parsing and recognition of hand-sketched diagrams
A long standing challenge in pen-based computer interaction is the ability to make sense of informal sketches. A main difficulty lies in reliably extracting and recognizing the i...
Levent Burak Kara, Thomas F. Stahovich
CVPR
2010
IEEE
15 years 9 months ago
Learning Mid-Level Features For Recognition
Many successful models for scene or object recognition transform low-level descriptors (such as Gabor filter responses, or SIFT descriptors) into richer representations of interme...
Y-Lan Boureau, Francis Bach, Yann LeCun, Jean Ponc...
WOWMOM
2009
ACM
180views Multimedia» more  WOWMOM 2009»
15 years 8 months ago
OPPORTUNITY: Towards opportunistic activity and context recognition systems
Opportunistic sensing allows to efficiently collect information about the physical world and the persons behaving in it. This may mainstream human context and activity recognitio...
Daniel Roggen, Kilian Förster, Alberto Calatr...
CIKM
1999
Springer
15 years 5 months ago
Word Segmentation and Recognition for Web Document Framework
It is observed that a better approach to Web information understanding is to base on its document framework, which is mainly consisted of (i) the title and the URL name of the pag...
Chi-Hung Chi, Chen Ding, Andrew Lim