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TRECVID
2008
13 years 11 months ago
Learning TRECVID'08 High-Level Features from YouTube
Run No. Run ID Run Description infMAP (%) training on TV08 data 1 IUPR-TV-M SIFT visual words with maximum entropy 6.1 2 IUPR-TV-MF SIFT with maximum entropy, fused with color+tex...
Adrian Ulges, Christian Schulze, Markus Koch, Thom...
BMCBI
2006
141views more  BMCBI 2006»
13 years 10 months ago
Identification of consensus RNA secondary structures using suffix arrays
Background: The identification of a consensus RNA motif often consists in finding a conserved secondary structure with minimum free energy in an ensemble of aligned sequences. How...
Mohammad Anwar, Truong Nguyen, Marcel Turcotte
BMCBI
2007
102views more  BMCBI 2007»
13 years 10 months ago
Setting up a large set of protein-ligand PDB complexes for the development and validation of knowledge-based docking algorithms
Background: The number of algorithms available to predict ligand-protein interactions is large and ever-increasing. The number of test cases used to validate these methods is usua...
Luis A. Diago, Persy Morell, Longendri Aguilera, E...
NN
2002
Springer
115views Neural Networks» more  NN 2002»
13 years 9 months ago
A self-organising network that grows when required
The ability to grow extra nodes is a potentially useful facility for a self-organising neural network. A network that can add nodes into its map space can approximate the input sp...
Stephen Marsland, Jonathan Shapiro, Ulrich Nehmzow
PAMI
2010
205views more  PAMI 2010»
13 years 8 months ago
Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing
In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical defor...
Long Zhu, Yuanhao Chen, Alan L. Yuille