Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: New algorithms for joint learning of independent component analysis and graphical high-order correlation (GC-ICA: Graphically Correlated ICA) are presented. The presented method has a fixed point style or of the FastICA, hover, it comprises independent but correlated subparts. Correlations by teacher signals are also allod. In spite of such inclusion of the dependency, the presented algorithm shows fast convergence. The converged set of bases has reduced indeterminacy on the ordering. This is equivalent to a self-organization of bases. This method can be used to analyze multiple images simultaneously. Examples are given on images from 3D- stereo videos shots. The correlation of bases on left and right eye views is shown for the first time here. Further speedup using the strategy of the RapidICA is possible.
['Ryota Yokote', 'Toshikazu Nakamura', 'Yasuo Matsuyama']
I am writing a research paper on a idea Independent component analysis with graphical correlation: Applications to multi-vision coding
[{"from": "human", "value": "I am writing a research paper on a idea Independent component analysis with graphical correlation: Applications to multi-vision coding"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: New algorithms for joint learning of independent component analysis and graphical high-order correlation (GC-ICA: Graphically Correlated ICA) are presented. The presented method has a fixed point style or of the FastICA, hover, it comprises independent but correlated subparts. Correlations by teacher signals are also allod. In spite of such inclusion of the dependency, the presented algorithm shows fast convergence. The converged set of bases has reduced indeterminacy on the ordering. This is equivalent to a self-organization of bases. This method can be used to analyze multiple images simultaneously. Examples are given on images from 3D- stereo videos shots. The correlation of bases on left and right eye views is shown for the first time here. Further speedup using the strategy of the RapidICA is possible."}]