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» Co-Tracking Using Semi-Supervised Support Vector Machines
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IJCNN
2007
IEEE
15 years 6 months ago
A Hardware-friendly Support Vector Machine for Embedded Automotive Applications
— We present here a hardware–friendly version of the Support Vector Machine (SVM), which is useful to implement its feed–forward phase on limited–resources devices such as ...
Davide Anguita, Alessandro Ghio, Stefano Pischiutt...
ML
2010
ACM
181views Machine Learning» more  ML 2010»
14 years 10 months ago
Decomposing the tensor kernel support vector machine for neuroscience data with structured labels
Abstract The tensor kernel has been used across the machine learning literature for a number of purposes and applications, due to its ability to incorporate samples from multiple s...
David R. Hardoon, John Shawe-Taylor
ICPR
2006
IEEE
16 years 29 days ago
Mixture of Support Vector Machines for HMM based Speech Recognition
Speech recognition is usually based on Hidden Markov Models (HMMs), which represent the temporal dynamics of speech very efficiently, and Gaussian mixture models, which do non-opt...
Sven E. Krüger, Martin Schafföner, Marce...
ICIP
2000
IEEE
16 years 1 months ago
Incorporate Support Vector Machines to Content-Based Image Retrieval with Relevant Feedback
By using relevance feedback [6], Content-Based Image Retrieval (CBIR) allows the user to retrieve images interactively. The user can select the most relevant images and provide a ...
Pengyu Hong, Qi Tian, Thomas S. Huang
ICDM
2002
IEEE
133views Data Mining» more  ICDM 2002»
15 years 4 months ago
Learning with Progressive Transductive Support Vector Machine
Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...
Yisong Chen, Guoping Wang, Shihai Dong