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» Evaluating learning algorithms and classifiers
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CVPR
2006
IEEE
14 years 10 months ago
BoostMotion: Boosting a Discriminative Similarity Function for Motion Estimation
Motion estimation for applications where appearance undergoes complex changes is challenging due to lack of an appropriate similarity function. In this paper, we propose to learn ...
Shaohua Kevin Zhou, Bogdan Georgescu, Dorin Comani...
SIGIR
2006
ACM
14 years 2 months ago
Large scale semi-supervised linear SVMs
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Vikas Sindhwani, S. Sathiya Keerthi
ICCV
2007
IEEE
14 years 10 months ago
Gradient Feature Selection for Online Boosting
Boosting has been widely applied in computer vision, especially after Viola and Jones's seminal work [23]. The marriage of rectangular features and integral-imageenabled fast...
Ting Yu, Xiaoming Liu 0002
KDD
2007
ACM
566views Data Mining» more  KDD 2007»
14 years 9 months ago
IMDS: intelligent malware detection system
The proliferation of malware has presented a serious threat to the security of computer systems. Traditional signature-based antivirus systems fail to detect polymorphic and new, ...
Yanfang Ye, Dingding Wang, Tao Li, Dongyi Ye
TMI
2002
248views more  TMI 2002»
13 years 8 months ago
Adaptive Elastic Segmentation of Brain MRI via Shape Model Guided Evolutionary Programming
This paper presents a fully automated segmentation method for medical images. The goal is to localize and parameterize a variety of types of structure in these images for subsequen...
Alain Pitiot, Arthur W. Toga, Paul M. Thompson