METHODS AND SYSTEMS FOR DATA ANALYSIS AND FEATURE RECOGNITION
First Claim
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1. A method for training one or more data sets for use in data analysis and feature recognition, the method comprising:
- processing one or more algorithms on a previously defined region of interest in a first data set for identifying a feature; and
storing the results of processing as the feature.
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Abstract
Systems and methods for automated pattern recognition and object detection. The method can be rapidly developed and improved using a minimal number of algorithms for the data content to fully discriminate details in the data, while reducing the need for human analysis. The system includes a data analysis system that recognizes patterns and detects objects in data without requiring adaptation of the system to a particular application, environment, or data content. The system evaluates the data in its native form independent of the form of presentation or the form of the post-processed data.
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Citations
20 Claims
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1. A method for training one or more data sets for use in data analysis and feature recognition, the method comprising:
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processing one or more algorithms on a previously defined region of interest in a first data set for identifying a feature; and storing the results of processing as the feature. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A system training one or more data sets for use in data analysis and feature recognition, the system comprising:
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a datastore; a display; and a processor in data communication with the display and the datastore, configured to automatically train the feature based on a first series of algorithms executed on a region of interest in a first data set and save the results of the training as the feature in the datastore. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A method for data analysis and feature recognition comprising:
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receiving a first data set; and identifying a feature in the received data set using results of a series of algorithms processed on a second data set, wherein identifying the feature further comprises; generating an algorithm value cache for the first data set; selecting a first target data element in a region of interest in the first data set; comparing the algorithm value cache for the first data set to the processed first series of algorithms on the second data set; and performing a feature processing action if there is match based on the comparison. - View Dependent Claims (16, 17)
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18. A system for data analysis and feature recognition comprising:
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a datastore configured to contain processed results of a first series of algorithms performed on a first data set; a display; and a processor in data communication with the display and the datastore, the processor comprising; a component configured to identify a feature in a second data set using the datastore, the component comprising; a first sub-component configured to generate an algorithm value cache for the second data set; a second sub-component configured to select a first target data element in a region of interest in the second data set; a third sub-component configured to compare the set of algorithm values to the processed set of algorithms in the datastore; and a fourth sub-component configured to perform a feature processing action if there is match between the second set of algorithm values and the first set of algorithm values in the datastore. - View Dependent Claims (19, 20)
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Specification