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» Robust Learning - Rich and Poor
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CCIA
2007
Springer
15 years 11 months ago
An Evaluation of an Object Recognition Schema Using Multiple Region Detectors
Abstract. Robust object recognition is one of the most challenging topics in computer vision. In the last years promising results have been obtained using local regions and descrip...
Meritxell Vinyals, Arnau Ramisa, Ricardo Toledo
CEAS
2004
Springer
15 years 10 months ago
The Impact of Feature Selection on Signature-Driven Spam Detection
Signature-driven spam detection provides an alternative to machine learning approaches and can be very effective when near-duplicates of essentially the same message are sent in h...
Aleksander Kolcz, Abdur Chowdhury, Joshua Alspecto...
138
Voted
DIS
2004
Springer
15 years 10 months ago
Mining Noisy Data Streams via a Discriminative Model
The two main challenges typically associated with mining data streams are concept drift and data contamination. To address these challenges, we seek learning techniques and models ...
Fang Chu, Yizhou Wang, Carlo Zaniolo
ECCV
2002
Springer
16 years 6 months ago
A Tale of Two Classifiers: SNoW vs. SVM in Visual Recognition
Numerous statistical learning methods have been developed for visual recognition tasks. Few attempts, however, have been made to address theoretical issues, and in particular, stud...
Ming-Hsuan Yang, Dan Roth, Narendra Ahuja
176
Voted
ICCV
2007
IEEE
15 years 11 months ago
Co-Tracking Using Semi-Supervised Support Vector Machines
This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...
Feng Tang, Shane Brennan, Qi Zhao, Hai Tao