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Network compensation for missing sensorsA network learning translation invariance algorithm to compute interpolation functions is presented. This algorithm with one fixed receptive field can construct a linear transformation compensating for gain changes, sensor position jitter, and sensor loss when there are enough remaining sensors to adequately sample the input images. However, when the images are undersampled and complete compensation is not possible, the algorithm need to be modified. For moderate sensor losses, the algorithm works if the transformation weight adjustment is restricted to the weights to output units affected by the loss.
Document ID
19930041368
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Ahumada, Albert J., Jr.
(NASA Ames Research Center Moffett Field, CA, United States)
Mulligan, Jeffrey B.
(NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
August 16, 2013
Publication Date
January 1, 1991
Publication Information
Publication: In: Human vision, visual processing, and digital display II; Proceedings of the Meeting, San Jose, CA, Feb. 27-Mar. 1, 1991 (A93-25363 08-54)
Publisher: Society of Photo-Optical Instrumentation Engineers
Subject Category
Cybernetics
Accession Number
93A25365
Funding Number(s)
PROJECT: RTOP 506-71-51
Distribution Limits
Public
Copyright
Other

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