MULTI-LEVEL INTROSPECTION FRAMEWORK FOR EXPLAINABLE REINFORCEMENT LEARNING AGENTS

    公开(公告)号:US20200320435A1

    公开(公告)日:2020-10-08

    申请号:US16842265

    申请日:2020-04-07

    Abstract: Techniques are disclosed for applying a multi-level introspection framework to interaction data characterizing a history of interaction of a reinforcement learning agent with an environment. The framework may apply statistical analysis and machine learning methods to interaction data collected during the RL agent's interaction with the environment. The framework may include a first (“environment”) level that analyzes characteristics of one or more tasks to be solved by the RL agent to generate elements, a second (“interaction”) level that analyzes actions of the RL agent when interacting with the environment to generate elements, and a third (“meta-analysis”) level that generates elements by analyzing combinations of elements generated by the first level and elements generated by the second level.

    INTEGRATED CIRCUIT IMAGE ALIGNMENT AND STITCHING

    公开(公告)号:US20200302584A1

    公开(公告)日:2020-09-24

    申请号:US16390885

    申请日:2019-04-22

    Abstract: In general, techniques are described for processing a set of high-resolution images of an integrated circuit, the images captured at different locations with respect to the integrated circuit, to automatically align and “stitch” the set of high-resolution images into a larger composite image. For example, an imaging system as described herein may use sampled feature points distributed across different grid tiles within overlap regions for pairs of images to match feature points to inform the alignments of a pair with respect to each image in the pair. The system may in some cases further apply a bundle adjustment to iteratively align and refine the alignment results for each image in a set of images being processed. In some examples, the bundle adjustment is a best-fit adjustment based on minimizing the net error associated with the alignment of the set of images.

    Time-frequency convolutional neural network with bottleneck architecture for query-by-example processing

    公开(公告)号:US10777188B2

    公开(公告)日:2020-09-15

    申请号:US16191296

    申请日:2018-11-14

    Abstract: A computing system determines whether a reference audio signal contains a query. A time-frequency convolutional neural network (TFCNN) comprises a time and frequency convolutional layers and a series of additional layers, which include a bottleneck layer. The computation engine applies the TFCNN to samples of a query utterance at least through the bottleneck layer. A query feature vector comprises output values of the bottleneck layer generated when the computation engine applies the TFCNN to the samples of the query utterance. The computation engine also applies the TFCNN to samples of the reference audio signal at least through the bottleneck layer. A reference feature vector comprises output values of the bottleneck layer generated when the computation engine applies the TFCNN to the samples of the reference audio signal. The computation engine determines at least one detection score based on the query feature vector and the reference feature vector.

    Method and system for monitoring driving behaviors

    公开(公告)号:US10769459B2

    公开(公告)日:2020-09-08

    申请号:US15751339

    申请日:2016-08-30

    Abstract: A method and a system are provided for monitoring driving conditions. The method includes receiving video data comprising video frames from one or more sensors where the video frames may represent an interior or exterior of a vehicle, detecting and recognizing one or more features from the video data where each feature is associated with at least one driving condition, extracting the one or more features from the video data, developing intermediate features by associating and aggregating the extracted features among the extracted features, and developing a semantic meaning for the at least one driving condition by utilizing the intermediate features and the extracted one or more features.

    CORTICAL STEGANOGRAPHY
    67.
    发明申请

    公开(公告)号:US20200273375A1

    公开(公告)日:2020-08-27

    申请号:US16775581

    申请日:2020-01-29

    Abstract: A machine and its modules assist in steganography for an animal. A steganography module applies behavioral sequencing to create a cover message and a hidden message to covertly pass information from one animal to another animal, with the information embedded in an individual's brain. A visual module references the steganography module to cause a sequence of visual images on a display screen to guide a motor sequence of an individual as the cover message as well as detect and communicate a timing of the individual's motor sequence, relative in timing, to visual images in the sequence of visual images being displayed on the display screen, in order to train in the cover message and hidden message. The hidden message is then extracted at a destination from a sensor monitoring the individual's sequence of motor actions.

    HEALTH MANAGEMENT SYSTEM
    69.
    发明申请

    公开(公告)号:US20200227161A1

    公开(公告)日:2020-07-16

    申请号:US16744962

    申请日:2020-01-16

    Abstract: In general, this disclosure describes techniques for a health management system that schedules medical appointments based on a dialog with a user (e.g., a patient), clinical guideline information, and/or other information. The health management system may engage in a dialog with the user, the dialog including requests from the health management system for audio input to the user device and audio input from the user in response to each request. The health management system may extract information from the audio input and compare the extracted information to clinical guideline information to determine one or more probable health conditions of the user. The health management system may determine a time allotment, identify a health care provider type and a platform for a medical appointment based on the one or more probable health conditions.

    Unclonable RFID chip and method
    70.
    发明授权

    公开(公告)号:US10664625B2

    公开(公告)日:2020-05-26

    申请号:US15542469

    申请日:2016-01-06

    Inventor: Michael G. Kane

    Abstract: A device includes a substrate, an array of metal pads on a first surface of the substrate, a carbon polymer composite covering the array of metal pads, the composite having variations that result in random resistance values between the metal pads usable as a random code. A method of manufacturing a secure device, including forming an array of metal pads on a dielet substrate, the dielet substrate containing at least one memory in which is stored an encryption key, and an RF communication section, covering the array of metal pads with a carbon polymer composite such that variations in the carbon concentration in the polymer forms a unique pattern of resistance, attaching the dielet substrate to a host component, receiving a request from a security server for a unique code determined by the unique pattern of resistance, and using the encryption key, encrypting and providing the unique code to the security server.

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