Abstract: Pedestrian activity recognition is embodied in a method, system, non-transitory computer-readable and vehicle. A Siamese neural network is trained to recognize a plurality of pedestrian activities by training it recordings of the same pedestrian activity from two or more separate training image capture devices. The Siamese neural network is deployed with continual data collection from an additional image capture device to create a dataset of clusters of similar activities in an unsupervised manner. A spatio-temporal intent prediction model is then trained that can be deployed to recognize and predict pedestrian activity. Based on the likelihood of a particular pedestrian activity occurring or currently being underway, an automatic vehicle maneuver can be executed to navigate the situation.

Abstract: A system and methodologies for neuromorphic (NM) vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking so as to detect and predict movement of a vehicle occupant.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking so as to detect and predict movement of a vehicle occupant.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.

Abstract: A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking.

Abstract: A method comprises obtaining, by a computer, patient information associated with a patient and operator information associated with one or more biometric sensors; determining, by the computer, a protocol for obtaining patient data from the patient based on the patient information and the operator information; obtaining, by the one or more biometric sensors, the patient data from the patient based on the protocol.

Abstract: A computer includes one or more processors; and logic coupled to the one or more processors and comprising one or more stored sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform: collecting first patient data, associated with at least one attribute, from a patient by one or more biometric sensors based on a first protocol; evaluating the first patient data based at least on a portion, of aggregate medical information, associated with the at least one attribute; based on the evaluating, determining a second protocol for collecting additional patient data; collecting the additional patient data by the one or more biometric sensors based on the second protocol.

Abstract: In an embodiment, a computer includes one or more processors; a computer readable storage medium comprising a sequence of instructions, which when executed by the one or more processors, cause: transmitting, to a second computer over a network, a first subset of patient data; receiving, from the second computer, a command for additional data, wherein the command is based on the first subset of the patient data; identifying a second subset of the patient data based on the command; transmitting, to the second computer, the second subset of the patient data; wherein the first subset of the patient data and the second subset of the patient data were collected by one or more biometric sensors within a same medical examination session.

Abstract: In an embodiment, precise measurement on a mobile computing device is facilitated with a computer comprising one or more processors; a computer readable storage medium comprising a sequence of instructions, which when executed by the one or more processors, cause the one or more processors to perform displaying, in a touch-sensitive computer display unit: an image of an object; over the image, a first reticle at a first position and a second reticle at a second position that is spaced apart from the first position; a measurement value representing a linear distance between the first reticle and the second reticle with reference to the object; one or more fine positioning icons each associated with a different direction; obtaining a selection of one of the first reticle and the second reticle as a selected reticle; obtaining user input selecting one of the fine positioning icons; in response to the user input, re-displaying the selected reticle in a new position in a particular direction associated with the se