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AIA
2006
13 years 9 months ago
Recurrent and Concurrent Neural Networks for Objects Recognition
A system based on a neural network framework is considered. We used two neural networks, an Elman network [1][2] and a Kohonen (concurrent) network [3], for a categorization task....
Federico Cecconi, Marco Campenní
CLOR
2006
13 years 11 months ago
A Sparse Object Category Model for Efficient Learning and Complete Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a weakly-supervised manner: the model is learnt from examp...
Robert Fergus, Pietro Perona, Andrew Zisserman
SSIAI
2002
IEEE
14 years 16 days ago
Geometry-Based Automatic Object Localization and 3-D Pose Detection
Given the image of a real-world scene and a polygonal 3-D model of a depicted object, its apparent size, image coordinates, and 3-D orientation are autonomously detected. Based on...
Marcus A. Magnor
3DIM
1999
IEEE
13 years 12 months ago
Large Data Sets and Confusing Scenes in 3-D Surface Matching and Recognition
In this paper, we report on recent extensions to a surface matching algorithm based on local 3-D signatures. This algorithm was previously shown to be effective in view registrati...
Owen T. Carmichael, Daniel F. Huber, Martial Heber...
IROS
2009
IEEE
120views Robotics» more  IROS 2009»
14 years 2 months ago
Interactive learning of visually symmetric objects
— This paper describes a robotic system that learns visual models of symmetric objects autonomously. Our robot learns by physically interacting with an object using its end effec...
Wai Ho Li, Lindsay Kleeman