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TSMC
2008
172views more  TSMC 2008»
9 years 1 days ago
AdaBoost-Based Algorithm for Network Intrusion Detection
Abstract--Network intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. It is an indispensable part of the information security sy...
Weiming Hu, Wei Hu, Stephen J. Maybank
TCSV
2008
313views more  TCSV 2008»
9 years 1 days ago
Fast Pedestrian Detection Using a Cascade of Boosted Covariance Features
Efficiently and accurately detecting pedestrians plays a very important role in many computer vision applications such as video surveillance and smart cars. In order to find the ri...
Sakrapee Paisitkriangkrai, Chunhua Shen, Jian Zhan...
PRL
2008
213views more  PRL 2008»
9 years 2 days ago
Boosting recombined weak classifiers
Boosting is a set of methods for the construction of classifier ensembles. The differential feature of these methods is that they allow to obtain a strong classifier from the comb...
Juan José Rodríguez, Jesús Ma...
NIPS
1996
9 years 1 months ago
Combinations of Weak Classifiers
To obtain classification systems with both good generalizat`ion performance and efficiency in space and time, we propose a learning method based on combinations of weak classifiers...
Chuanyi Ji, Sheng Ma
ECCV
2006
Springer
9 years 2 months ago
Recognition and Segmentation of 3-D Human Action Using HMM and Multi-class AdaBoost
Our goal is to automatically segment and recognize basic human actions, such as stand, walk and wave hands, from a sequence of joint positions or pose angles. Such recognition is d...
Fengjun Lv, Ramakant Nevatia
EVOW
2000
Springer
9 years 3 months ago
Combining Evolutionary, Connectionist, and Fuzzy Classification Algorithms for Shape Analysis
This paper presents an investigation into the classification of a difficult data set containing large intra-class variability but low inter-class variability. Standard classifiers...
Paul L. Rosin, Henry O. Nyongesa
AVBPA
2003
Springer
133views Biometrics» more  AVBPA 2003»
9 years 3 months ago
LUT-Based Adaboost for Gender Classification
There are two main approaches to the problem of gender classification, Support Vector Machines (SVMs) and Adaboost learning methods, of which SVMs are better in correct rate but ar...
Bo Wu, Haizhou Ai, Chang Huang
FGR
2004
IEEE
161views Biometrics» more  FGR 2004»
9 years 3 months ago
AdaBoost with Totally Corrective Updates for Fast Face Detection
An extension of the AdaBoost learning algorithm is proposed and brought to bear on the face detection problem. In each weak classifier selection cycle, the novel totally correctiv...
Jan Sochman, Jiri Matas
IWBRS
2005
Springer
168views Biometrics» more  IWBRS 2005»
9 years 5 months ago
Gabor Feature Selection for Face Recognition Using Improved AdaBoost Learning
Though AdaBoost has been widely used for feature selection and classifier learning, many of the selected features, or weak classifiers, are redundant. By incorporating mutual infor...
LinLin Shen, Li Bai, Daniel Bardsley, Yangsheng Wa...
WWW
2005
ACM
10 years 25 days ago
Boosting SVM classifiers by ensemble
By far, the support vector machines (SVM) achieve the state-of-theart performance for the text classification (TC) tasks. Due to the complexity of the TC problems, it becomes a ch...
Yan-Shi Dong, Ke-Song Han
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