A layout-conscious iteration space transformation technique

2001 ◽  
Vol 50 (12) ◽  
pp. 1321-1335 ◽  
Author(s):  
M. Kandemir ◽  
J. Ramanujam ◽  
A. Choudhary ◽  
P. Banerjee
Keyword(s):  
Transformation Technique ◽  
Iteration Space ◽  
Space Transformation

scholarly journals A sparse iteration space transformation framework for sparse tensor algebra

2020 ◽  
Vol 4 (OOPSLA) ◽  
pp. 1-30 ◽  
Author(s):  
Ryan Senanayake ◽  
Changwan Hong ◽  
Ziheng Wang ◽  
Amalee Wilson ◽  
Stephen Chou ◽  
...  
Keyword(s):  
Tensor Algebra ◽  
Iteration Space ◽  
Space Transformation

scholarly journals An efficient adaptive beam-space transformation technique and its application in array processing

2015 ◽  
Vol 64 (9) ◽  
pp. 094304
Author(s):  
Fan Zhan ◽  
Liang Guo-Long ◽  
Wang Jin-Jin ◽  
Wang Yan ◽  
Tao Kai
Keyword(s):  
Array Processing ◽  
Transformation Technique ◽  
Space Transformation

Color Space Transformation using Neural Networks

2019 ◽  
Vol 2019 (1) ◽  
pp. 153-158
Author(s):  
Lindsay MacDonald
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Color Space ◽  
Reflectance Spectra ◽  
Network Architectures ◽  
Color Spaces ◽  
Natural Materials ◽  
Space Transformation ◽  
Color Space Transformation

We investigated how well a multilayer neural network could implement the mapping between two trichromatic color spaces, specifically from camera R,G,B to tristimulus X,Y,Z. For training the network, a set of 800,000 synthetic reflectance spectra was generated. For testing the network, a set of 8,714 real reflectance spectra was collated from instrumental measurements on textiles, paints and natural materials. Various network architectures were tested, with both linear and sigmoidal activations. Results show that over 85% of all test samples had color errors of less than 1.0 ΔE2000 units, much more accurate than could be achieved by regression.

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