Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection
An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using a combinatorial algorithm.
- Issue Date:
- OSTI Identifier:
- Los Alamos National Security, LLC (Los Alamos, NM) LANL
- Patent Number(s):
- Application Number:
- Contract Number:
- Resource Relation:
- Patent File Date: 2015 Jul 22
- Research Org:
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Sponsoring Org:
- Country of Publication:
- United States
- 99 GENERAL AND MISCELLANEOUS; 97 MATHEMATICS AND COMPUTING
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A feedforward architecture accounts for rapid categorization
journal, April 2007
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- Proceedings of the National Academy of Sciences, Vol. 104, Issue 15, p. 6424-6429
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