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» Sampling Methods for Unsupervised Learning
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94
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BMCBI
2010
208views more  BMCBI 2010»
14 years 11 months ago
Using machine learning to speed up manual image annotation: application to a 3D imaging protocol for measuring single cell gene
Background: Image analysis is an essential component in many biological experiments that study gene expression, cell cycle progression, and protein localization. A protocol for tr...
Zafer Aydin, John I. Murray, Robert H. Waterston, ...
83
Voted
ESEM
2008
ACM
15 years 27 days ago
Some lessons learned in conducting software engineering surveys in china
Component-Based Software Engineering (CBSE) with Open Source Software and Commercial-Off-the-Shelf (COTS) components, Open Source Software (OSS) based development, and Software Ou...
Junzhong Ji, Jingyue Li, Reidar Conradi, Chunnian ...
BMCBI
2010
133views more  BMCBI 2010»
14 years 11 months ago
Improving de novo sequence assembly using machine learning and comparative genomics for overlap correction
Background: With the rapid expansion of DNA sequencing databases, it is now feasible to identify relevant information from prior sequencing projects and completed genomes and appl...
Lance E. Palmer, Mathäus Dejori, Randall A. B...
80
Voted
CVPR
2007
IEEE
16 years 1 months ago
Parameter Sensitive Detectors
Object detection can be challenging when the object class exhibits large variations. One commonly-used strategy is to first partition the space of possible object variations and t...
Quan Yuan, Ashwin Thangali, Vitaly Ablavsky, Stan ...
99
Voted
SADM
2010
141views more  SADM 2010»
14 years 5 months ago
A parametric mixture model for clustering multivariate binary data
: The traditional latent class analysis (LCA) uses a mixture model with binary responses on each subject that are independent conditional on cluster membership. However, in many pr...
Ajit C. Tamhane, Dingxi Qiu, Bruce E. Ankenman