Login Form






Lost Password?
Home
Who are we?
Image 

Artificial Intelligence for Investigating Anti-cancer solutions 

We are on a mission to investigate and provide the most advanced Machine Learning and Web Intelligence technologies to find treatments or diagnostic tools to fight diseases like cancers. 

 

Download CHO and Vero images here!

 
Quantification and Calibration of Collective Morphological Differences in Cell Images

Quantifying a wide variety of morphological differences observed in cell images under different drug influences is still a challenging task because the result can be highly sensitive to sampling and noise. We propose a graph-based approach to cell image analysis. We define graph transition energy to quantify morphological differences between image sets. A spectral graph theoretic regularization is applied to transform the feature space based on training examples of extremely different images to calibrate the quantification.

Read more...
 
Online Learning: Periodic Step Size Adaptation (PSA) (2007-)

Periodic Step size Adaptation (PSA) is an on-line learning algorithm that can reach near-optimal empirical performance in a single-pass through training data. PSA can be applied to train a wide variety of models, including CRF and SVM. Source codes are released on October 15, 2009. Description of PSA can be found in NIPS*2009 [PDF] and Machine Learning Journal [PDF] .

Read more...
 
<< Start < Prev 1 2 Next > End >>

Results 1 - 4 of 6
© 2014 Artificial Intelligence for Investigating Anti-cancer solutions