Mechanism discovery and model identification using genetic feature extraction and statistical testing

2020 ◽  
Vol 140 ◽  
pp. 106900
Author(s):  
Arijit Chakraborty ◽  
Abhishek Sivaram ◽  
Lakshminarayanan Samavedham ◽  
Venkat Venkatasubramanian
2011 ◽  
Vol 196 (1) ◽  
pp. 151-158 ◽  
Author(s):  
Yang Li ◽  
Hua-Liang Wei ◽  
Stephen A. Billings ◽  
P.G. Sarrigiannis

Author(s):  
J.P. Fallon ◽  
P.J. Gregory ◽  
C.J. Taylor

Quantitative image analysis systems have been used for several years in research and quality control applications in various fields including metallurgy and medicine. The technique has been applied as an extension of subjective microscopy to problems requiring quantitative results and which are amenable to automatic methods of interpretation.Feature extraction. In the most general sense, a feature can be defined as a portion of the image which differs in some consistent way from the background. A feature may be characterized by the density difference between itself and the background, by an edge gradient, or by the spatial frequency content (texture) within its boundaries. The task of feature extraction includes recognition of features and encoding of the associated information for quantitative analysis.Quantitative Analysis. Quantitative analysis is the determination of one or more physical measurements of each feature. These measurements may be straightforward ones such as area, length, or perimeter, or more complex stereological measurements such as convex perimeter or Feret's diameter.


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