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CVPR
2009
IEEE
15 years 2 months ago
Unsupervised Learning of Hierarchical Spatial Structures In Images
The visual world demonstrates organized spatial patterns, among objects or regions in a scene, object-parts in an object, and low-level features in object-parts. These classes o...
Devi Parikh (Carnegie Mellon University), C. Lawre...
SSPR
2004
Springer
14 years 29 days ago
Learning from General Label Constraints
Most machine learning algorithms are designed either for supervised or for unsupervised learning, notably classification and clustering. Practical problems in bioinformatics and i...
Tijl De Bie, Johan A. K. Suykens, Bart De Moor
ICCV
2005
IEEE
14 years 9 months ago
Efficient Learning of Relational Object Class Models
We present an efficient method for learning part-based object class models from unsegmented images represented as sets of salient features. A model includes parts' appearance...
Aharon Bar-Hillel, Tomer Hertz, Daphna Weinshall
CVPR
2004
IEEE
14 years 9 months ago
Is Bottom-Up Attention Useful for Object Recognition?
A key problem in learning multiple objects from unlabeled images is that it is a priori impossible to tell which part of the image corresponds to each individual object, and which...
Ueli Rutishauser, Dirk Walther, Christof Koch, Pie...
ICCV
2009
IEEE
15 years 18 days ago
What is the Best Multi-Stage Architecture for Object Recognition?
In many recent object recognition systems, feature extraction stages are generally composed of a filter bank, a non-linear transformation, and some sort of feature pooling layer...
Kevin Jarrett, Koray Kavukcuoglu, Marc’Aurelio R...