State of the art protein-protein interaction prediction

sp-Cov features pool image regions into a combine covariance feature

sp-Cov features pool image regions into a combine covariance feature

In another indication that the Machine Learning behind most Computer Vision Problems has more general applicability, we have just had a paper accepted which shows that the approach we developed for pedestrian detection achieves the world’s best performance in predicting protein-protein interactions.

This result is based on the data set labelled ‘Physical Interaction Task in Detailed feature type’, published by CMU at http://www.cs.cmu.edu/~qyj/papers_sulp/proteins05_pages/feature-download.html

The paper is titled Pedestrian Detection with Spatially Pooled Features and Structured Ensemble Learning, by Sakrapee Paisitkriangkrai, Chunhua Shen, Anton van den Hengel, and has been accepted for publication in IEEE PAMI.

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