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IVC
2008
69views more  IVC 2008»
13 years 8 months ago
Unsupervised texture classification: Automatically discover and classify texture patterns
In this paper, we present a novel approach to classify texture collections. This approach does not require experts to provide annotated training set. Given the image collection, w...
Lei Qin, Qingfang Zheng, Shuqiang Jiang, Qingming ...
COMSUR
2008
108views more  COMSUR 2008»
13 years 9 months ago
A survey of techniques for internet traffic classification using machine learning
The research community has begun looking for IP traffic classification techniques that do not rely on `well known' TCP or UDP port numbers, or interpreting the contents of pac...
Thuy T. T. Nguyen, Grenville J. Armitage
LREC
2008
91views Education» more  LREC 2008»
13 years 10 months ago
Classification Procedures for Software Evaluation
We outline a methodological classification for evaluation approaches of software in general. This classification was initiated partly owing to involvement in a biennial European c...
Muriel Amar, Sophie David, Rachel Panckhurst, Lisa...
CORR
2008
Springer
127views Education» more  CORR 2008»
13 years 9 months ago
Intrusion Detection in Mobile Ad Hoc Networks Using Classification Algorithms
In this paper we present the design and evaluation of intrusion detection models for MANETs using supervised classification algorithms. Specifically, we evaluate the performance of...
Aikaterini Mitrokotsa, Manolis Tsagkaris, Christos...
CORR
2008
Springer
127views Education» more  CORR 2008»
13 years 9 months ago
Adaptive Base Class Boost for Multi-class Classification
We propose abc-boost (adaptive base class boost) for multi-class classification and present abc-mart, an implementation of abcboost, based on the multinomial logit model. The key ...
Ping Li