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ICML
2005
IEEE
14 years 8 months ago
Q-learning of sequential attention for visual object recognition from informative local descriptors
This work provides a framework for learning sequential attention in real-world visual object recognition, using an architecture of three processing stages. The first stage rejects...
Lucas Paletta, Gerald Fritz, Christin Seifert
SCIA
2005
Springer
211views Image Analysis» more  SCIA 2005»
14 years 1 months ago
Perception-Action Based Object Detection from Local Descriptor Combination and Reinforcement Learning
This work proposes to learn visual encodings of attention patterns that enables sequential attention for object detection in real world environments. The system embeds a saccadic d...
Lucas Paletta, Gerald Fritz, Christin Seifert
MANSCI
2006
180views more  MANSCI 2006»
13 years 7 months ago
Selectively Acquiring Customer Information: A New Data Acquisition Problem and an Active Learning-Based Solution
This paper presents a new information acquisition problem motivated by business applications where customer data has to be acquired with a specific modeling objective in mind. In ...
Zhiqiang Zheng, Balaji Padmanabhan
MIR
2004
ACM
236views Multimedia» more  MIR 2004»
14 years 1 months ago
Boosting contextual information in content-based image retrieval
We present a new framework for characterizing and retrieving objects in cluttered scenes. This CBIR system is based on a new representation describing every object taking into acc...
Jaume Amores, Nicu Sebe, Petia Radeva, Theo Gevers...
ECCV
2010
Springer
14 years 1 months ago
Localizing Objects while Learning Their Appearance
Learning a new object class from cluttered training images is very challenging when the location of object instances is unknown. Previous works generally require objects covering a...