150 search results - page 6 / 30 » Feature selection combining genetic algorithm and Adaboost c... |
ICIP
2010
IEEE
13 years 5 months ago
2010
IEEE
In this paper, we propose an approach for fast pedestrian detection in images. Inspired by the histogram of oriented gradient (HOG) features, a set of multi-scale orientation (MSO...
CVPR
2005
IEEE
14 years 9 months ago
2005
IEEE
We combine local texture features (PCA-SIFT), global features (shape context), and spatial features within a single multi-layer AdaBoost model of object class recognition. The fir...
IJCNN
2007
IEEE
14 years 1 months ago
2007
IEEE
— Although AdaBoost has achieved great success, it still suffers from following problems: (1) the training process could be unmanageable when the number of features is extremely ...
ECML
2003
Springer
14 years 19 days ago
2003
Springer
Comparative machine learning experiments have become an important methodology in empirical approaches to natural language processing (i) to investigate which machine learning algor...
GECCO
2007
Springer
14 years 1 months ago
2007
Springer
Selecting the most relevant factors from genetic profiles that can optimally characterize cellular states is of crucial importance in identifying complex disease genes and biomark...