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VLSID
2005
IEEE
105views VLSI» more  VLSID 2005»
14 years 1 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...
BIOCOMP
2006
13 years 9 months ago
Support Vector Machines for Predicting microRNA Hairpins
- microRNAs (miRNAs) are 20-22 nt noncoding RNAs which are rapidly emerging as crucial regulators of gene expression in plants and animals. Identification of the hairpins which yie...
Karol Szafranski, Molly Megraw, Martin Reczko, Art...
NIPS
2003
13 years 9 months ago
Phonetic Speaker Recognition with Support Vector Machines
A recent area of significant progress in speaker recognition is the use of high level features—idiolect, phonetic relations, prosody, discourse structure, etc. A speaker not on...
William M. Campbell, Joseph P. Campbell, Douglas A...
ICASSP
2008
IEEE
14 years 2 months ago
Hybrid feature selection for gesture recognition using support vector machines
This paper presents an approach for a multi-cue based two-dimensional gesture recognition that combines two different forms of cues, namely shape cues and motion cues, in a suppor...
Yu Yuan, Kenneth Barner
ISSRE
2005
IEEE
14 years 1 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