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ICCV
2005
IEEE
14 years 9 months ago
A Maximum Entropy Framework for Part-Based Texture and Object Recognition
This paper presents a probabilistic part-based approach for texture and object recognition. Textures are represented using a part dictionary found by quantizing the appearance of ...
Svetlana Lazebnik, Cordelia Schmid, Jean Ponce
CLOR
2006
13 years 11 months ago
A Discriminative Framework for Texture and Object Recognition Using Local Image Features
This chapter presents an approach for texture and object recognition that uses scale- or affine-invariant local image features in combination with a discriminative classifier. Text...
Svetlana Lazebnik, Cordelia Schmid, Jean Ponce
LREC
2010
165views Education» more  LREC 2010»
13 years 8 months ago
Maximum Entropy Classifier Ensembling using Genetic Algorithm for NER in Bengali
In this paper, we propose classifier ensemble selection for Named Entity Recognition (NER) as a single objective optimization problem. Thereafter, we develop a method based on gen...
Asif Ekbal, Sriparna Saha
CVPR
2009
IEEE
15 years 1 months ago
Learning Mixed Templates for Object Recognition
This article proposes a method for learning object templates composed of local sketches and local textures, and investigates the relative importance of the sketches and textures ...
Haifeng Gong, Song Chun Zhu, Ying Nian Wu, Zhangzh...
IROS
2007
IEEE
179views Robotics» more  IROS 2007»
14 years 1 months ago
Stereo-based 6D object localization for grasping with humanoid robot systems
Abstract— Robust vision-based grasping is still a hard problem for humanoid robot systems. When being restricted to using the camera system built-in into the robot’s head for o...
Pedram Azad, Tamim Asfour, Rüdiger Dillmann