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Saturday, March 17, 2018

Minimalist machine learning

‘Minimalist machine learning’ algorithm analyzes complex microscopy and other images from very little data
March 16, 2018

These are images of a slice of mouse lymphblastoid cells; a. is the raw data, b is the corresponding manual segmentation and c is the output of an MS-D network with 100 layers. (credit: Data from A. Ekman and C. Larabell, National Center for X-ray Tomography.) 
Key tool for Chan-Zuckerberg-sponsored Human Cell Atlas project
Mathematicians at Lawrence Berkeley National Laboratory (Berkeley Lab) have developed a radical new approach to machine learning: a new type of highly efficient “deep convolutional neural network” that can automatically analyze complex experimental scientific images from limited data.* As experimental facilities generate higher-resolution images at higher speeds, scientists struggle to manage and analyze the resulting … more…

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