Dynamic image recognition and training using data center resources and data
AssigneeDell Products L.P.
InventorsJeffrey M. Lairsey, Saurabh Kishore, Alexander P. Rote, Sudhir V. Shetty
Life of this patent
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Abstract
A system, method, and computer-readable medium are disclosed for creating image recognition models, which can be operated on smartphone or similar device. The smartphone captures images of hardware in a data center. The captured images are processed to produce a full set of annotated images. The full set is minimized to a simplified set and trained to create a mobile image recognition model implemented by the smartphone or similar device.
Claims20
A computer-implementable method for creating image recognition models, the method comprising:
- receiving captured images of hardware in a data center;
- processing the captured images to produce a full set of annotated captured images;
- minimizing the full set of annotated captured images with a template, wherein a minimum set of classifications based on pruning classifications in a master set of annotations is used to create a simplified set of images, wherein the pruning classifications is performed by identifying annotation patterns and applying multiple heuristics;
- and
- training the simplified set of images into a mobile image recognition model, to understand patterns on the original annotated captured images to predict location of the hardware in the data center.
A system comprising:
- a processor;
- a data bus coupled to the processor;
- and
- a non-transitory, computer-readable storage medium embodying computer program code, the non-transitory, computer-readable storage medium being coupled to the data bus, the computer program code interacting with a plurality of computer operations for creating image recognition models and comprising instructions executable by the processor and configured for:
- receiving captured images of hardware in a data center;
- processing the captured images to produce a full set of annotated captured images;
- minimizing the full set of annotated captured images with a template, wherein a minimum set of classifications based on pruning classifications in a master set of annotations is used to create a simplified set of images, wherein the pruning classifications is performed by identifying annotation patterns and applying multiple heuristics;
- and
- training the simplified set of images into a mobile image recognition model, to understand patterns on the original annotated captured images to predict location of the hardware in the data center.
A non-transitory, computer-readable storage medium embodying computer program code, the computer program code comprising computer executable instructions configured for:
- receiving captured images of hardware in a data center;
- processing the captured images to produce a full set of annotated captured images;
- minimizing the full set of annotated captured images with a template, wherein a minimum set of classifications based on pruning classifications in a master set of annotations is used to create a simplified set of images, wherein the pruning classifications is performed by identifying annotation patterns and applying multiple heuristics;
- and
- training the simplified set of images into a mobile image recognition model, to understand patterns on the original annotated captured images to predict location of the hardware in the data center.
Dependencies are inferred from the claim text.