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ICMCS
2008
IEEE
201views Multimedia» more  ICMCS 2008»
14 years 2 months ago
Logitboost weka classifier speech segmentation
Segmenting the speech signals on the basis of time-frequency analysis is the most natural approach. Boundaries are located in places where energy of some frequency subband rapidly...
Bartosz Ziólko, Suresh Manandhar, Richard C...
BMCBI
2008
93views more  BMCBI 2008»
13 years 8 months ago
Using iterative cluster merging with improved gap statistics to perform online phenotype discovery in the context of high-throug
Background: The recent emergence of high-throughput automated image acquisition technologies has forever changed how cell biologists collect and analyze data. Historically, the in...
Zheng Yin, Xiaobo Zhou, Chris Bakal, Fuhai Li, You...
ACL
2006
13 years 9 months ago
Segment-Based Hidden Markov Models for Information Extraction
Hidden Markov models (HMMs) are powerful statistical models that have found successful applications in Information Extraction (IE). In current approaches to applying HMMs to IE, a...
Zhenmei Gu, Nick Cercone
EMMCVPR
2005
Springer
14 years 1 months ago
Segmentation Informed by Manifold Learning
In many biomedical imaging applications, video sequences are captured with low resolution and low contrast challenging conditions in which to detect, segment, or track features. Wh...
Qilong Zhang, Richard Souvenir, Robert Pless
SIBGRAPI
2007
IEEE
14 years 2 months ago
White blood cell segmentation using morphological operators and scale-space analysis
Cell segmentation is a challenging problem due to both the complex nature of the cells and the uncertainty present in video microscopy. Manual methods for this purpose are onerous...
Leyza Baldo Dorini, Rodrigo Minetto, Neucimar Jer&...