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System and method for managing data privacy

A system and method for assessing the risk associated with the protection of data privacy by software application. A decision engine is provided to assess monitor and manage key issues around the risk management of data privacy. The system creates a core repository that manages, monitors and measures the data privacy assessments of applications across an institution (e.g., a corporation). The system and method employs automated questionnaires that require responses from the user (preferably the manager responsible for the application). The responses are tracked in order to evaluate the progress of the assessment and the status of the applications with respect to compliance with the enterprise's data privacy policies and procedures as well as the regulations and laws of the jurisdictions in which the application is operated. Once a questionnaire has been completed, the application is given ratings both with respect to the data privacy impact of the application and the application's compliance with the data privacy requirements. If a risk exists, a plan for reducing the risk or bringing the application into compliance can be formulated, and progress towards compliance can be tracked. Alternatively, an identified exposure to risk can be acknowledged through the system, which requires sign off by various higher level managers and administrators.

Systems and methods for recognizing objects in radar imagery

ActiveUS20160019458A1Low in size and weight and power requirementImprove historical speed and accuracy performance limitationDigital computer detailsDigital dataPattern recognitionGraphics
The present invention is directed to systems and methods for detecting objects in a radar image stream. Embodiments of the invention can receive a data stream from radar sensors and use a deep neural network to convert the received data stream into a set of semantic labels, where each semantic label corresponds to an object in the radar data stream that the deep neural network has identified. Processing units running the deep neural network may be collocated onboard an airborne vehicle along with the radar sensor(s). The processing units can be configured with powerful, high-speed graphics processing units or field-programmable gate arrays that are low in size, weight, and power requirements. Embodiments of the invention are also directed to providing innovative advances to object recognition training systems that utilize a detector and an object recognition cascade to analyze radar image streams in real time. The object recognition cascade can comprise at least one recognizer that receives a non-background stream of image patches from a detector and automatically assigns one or more semantic labels to each non-background image patch. In some embodiments, a separate recognizer for the background analysis of patches may also be incorporated. There may be multiple detectors and multiple recognizers, depending on the design of the cascade. Embodiments of the invention also include novel methods to tailor deep neural network algorithms to successfully process radar imagery, utilizing techniques such as normalization, sampling, data augmentation, foveation, cascade architectures, and label harmonization.
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