Retinal encoder for machine vision
AssigneeCornell University
InventorsSheila NIRENBERG, Illya Bomash
Life of this patent
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Abstract
A method is disclosed including: receiving raw image data corresponding to a series of raw images; processing the raw image data with an encoder to generate encoded data, where the encoder is characterized by an input/output transformation that substantially mimics the input/output transformation of one or more retinal cells of a vertebrate retina; and applying a first machine vision algorithm to data generated based at least in part on the encoded data.
Claims20
A method including:
- applying, by an encoding module, a spatiotemporal transformation to image data to generate retinal output cell response values;
- generating, by the encoding module, encoded data based on the retinal output cell response values;
- applying, by a machine vision module, a machine vision algorithm to the encoded data;
- monitoring, by a controller, performance of the machine vision algorithm;
- and
- adjusting, by the controller, the machine vision algorithm based on the monitored performance.
An apparatus including:
- a memory storage device configured to store image data corresponding to a series of images;
- and
- a processor operably coupled with the memory and programmed to:
- receive the image data corresponding to the series of images;
- generate encoded data from the image data, wherein the generating comprises:
- apply a spatiotemporal transformation to image data to generate retinal output cell response values;
- generate encoded data based on the retinal output cell response values;
- apply a machine vision algorithm to the encoded data;
- monitor performance of the machine vision algorithm;
- and
- adjust the machine vision algorithm based on the monitored performance.
A non-transitory computer-readable medium having computer-executable instructions for implementing operations comprising
- applying a spatiotemporal transformation to image data to generate retinal output cell response values;
- generating encoded data based on the retinal output cell response values;
- applying a machine vision algorithm to the encoded data;
- monitoring performance of the machine vision algorithm;
- and
- adjusting the machine vision algorithm based on the monitored performance.
Dependencies are inferred from the claim text.