DocumentCode
3040181
Title
Faster learning via optimised Adaboost
Author
Young, David P. ; Ferryman, James M.
Author_Institution
Dept. of Comput. Sci., Reading Univ., UK
fYear
2005
fDate
15-16 Sept. 2005
Firstpage
400
Lastpage
405
Abstract
Adaboost has been found by many researchers to be an extremely successful classification algorithm. However, it is often stated that Adaboost takes a significant amount of time to learn a good classification. This paper aims to show that the Adaboost algorithm is not the cause of the slow learning. By altering how Adaboost is used, a significant increase in learning speed, over 14 times faster, can be achieved at the cost of a small loss in classification accuracy.
Keywords
image classification; learning (artificial intelligence); classification algorithm; fast learning; optimised Adaboost; Classification algorithms; Computer science; Computer vision; Costs; Face detection; Filters; Neurons; Object detection; Resists; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Video and Signal Based Surveillance, 2005. AVSS 2005. IEEE Conference on
Print_ISBN
0-7803-9385-6
Type
conf
DOI
10.1109/AVSS.2005.1577302
Filename
1577302
Link To Document