Ricoh Company, Ltd.

Motili, Inc.

Ian Wilkins

Jeff Wilkins

James Bowman

Farnaz HajiahmadiFoomani

Systems and methods are provided for validating an autoencoder for a printing system. In one embodiment, a system stores values associated with individual features at a printing system and further stores times indicating when the values were determined at the printing system. The system also operates an autoencoder to perform time-compression upon the values and the times. Validating the autoencoder includes: determining predictive powers of the individual features prior to time-compression via partial F tests, determining predictive powers of the individual features after time-compression via partial F tests, and determining differences between the predictive powers of the individual features before time-compression and the predictive powers of the individual features after time-compression. Depending upon differences in the predictive powers, a report is generated indicating validity or invalidity of the autoencoder.

Validation of autoencoders that perform timestamp compression for printing system data

Systems and methods for computer-implemented pre-optimization of input data before further processing thereof by a computer-implemented analyzation process, such as optical character recognition (OCR). A cooperative model is employed that combines one or more supervised-learning based inspector sub-models, and one or more filter sub-models that operating in series with the inspector sub-model(s). The inspectors first receive the input data and calculate one predicted transformation parameters then used to perform transformations on the input data. The inspector-transformed data is then passed to the filters, which derive respective convolution kernels and apply same to the inspector-transformed data before passing same to the OCR or other analyzation process. The inspectors may be pretrained with different training data. For OCR, the model is trained on minimization of normalized edit distance, the inspectors apply initial warping transformations to text images, followed by application of filtering transformations and input to the OCR engine.

Methods and systems for pre-optimizing input data for an OCR engine or other computer-implemented analysis process

Systems and methods are provided for print quality management. One embodiment is a system for identifying print quality at a printer. The system includes a memory that stores reference data for nozzles of a printer, and a controller. The controller is configured to acquire measurement data after operation of the nozzles, calculate differences between the reference data and the measurement data, apply the differences as an input to an isolation forest, operate the isolation forest to determine isolation values for the nozzles, identify nozzles having more than a threshold amount of deviation from the reference data based on the isolation values, and generate a report flagging the identified nozzles for maintenance.

Detection of printhead conditions based on isolation scoring

A method for processing information regarding a climate-control device is provided. The method includes the steps of generating a virtual asset tag of the climate-control device; processing the virtual asset tag; and extracting information about the climate-control device from the virtual asset tag.

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Boulder, CO, United States of America

Ian Wilkins