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IJCNN
2006
IEEE
16 years 10 days ago
Support Vector Machines to Weight Voters in a Voting System of Entity Extractors
—Support Vector Machines are used to combine the outputs of multiple entity extractors, thus creating a composite entity extraction system. The composite system has a significant...
Deborah Duong, James Venuto, Ben Goertzel, Ryan Ri...
CSB
2005
IEEE
133views Bioinformatics» more  CSB 2005»
15 years 12 months ago
Investigation into Biomedical Literature Classification Using Support Vector Machines
Specific topic search in the PubMed Database, one of the most important information resources for scientific community, presents a big challenge to the users. The researcher typic...
Nalini Polavarapu, Shamkant B. Navathe, Ramprasad ...
ISSRE
2005
IEEE
15 years 12 months ago
A Novel Method for Early Software Quality Prediction Based on Support Vector Machine
The software development process imposes major impacts on the quality of software at every development stage; therefore, a common goal of each software development phase concerns ...
Fei Xing, Ping Guo, Michael R. Lyu
VLSID
2005
IEEE
105views VLSI» more  VLSID 2005»
15 years 12 months ago
Placement and Routing for 3D-FPGAs Using Reinforcement Learning and Support Vector Machines
The primary advantage of using 3D-FPGA over 2D-FPGA is that the vertical stacking of active layers reduce the Manhattan distance between the components in 3D-FPGA than when placed...
R. Manimegalai, E. Siva Soumya, V. Muralidharan, B...
CVBIA
2005
Springer
15 years 12 months ago
Segmenting Brain Tumors with Conditional Random Fields and Support Vector Machines
Abstract. Markov Random Fields (MRFs) are a popular and wellmotivated model for many medical image processing tasks such as segmentation. Discriminative Random Fields (DRFs), a dis...
Chi-Hoon Lee, Mark Schmidt, Albert Murtha, Aalo Bi...