Self-organized Learning of 3 Dimensions

Self-organized Learning of 3 Dimensions. Szepesvári, C. & Lörincz, A. In Marinaro, M. & Morasso, P., editors, ICANN, volume 2, pages 671–674, Sorrento, Italy, 1994. IEEE.

Paper abstract bibtex

The geometric learning capabilities of a competitive neural network are studied. It is shown that the appropriate selection of a neural activity function enables the learning of the 3D geometry of a world, from two of the 2D projections of 3D extended objects

@inproceedings{Szepesvari1994a,
	abstract = {The geometric learning capabilities of a competitive neural network are studied. It is shown that the appropriate selection of a neural activity function enables the learning of the 3D geometry of a world, from two of the 2D projections of 3D extended objects},
	address = {Sorrento, Italy},
	author = {Szepesv{\'a}ri, Cs. and L{\"o}rincz, A.},
	booktitle = {ICANN},
	editor = {Marinaro, M. and Morasso, P.G.},
	keywords = {manifold learning, theory, neural networks},
	pages = {671--674},
	publisher = {IEEE},
	title = {Self-organized Learning of 3 Dimensions},
	url_paper = {icann94.ps.pdf},
	volume = {2},
	year = {1994}}

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