Abstract: Provided herein are systems and methods for pairing a remote controller unit and a control unit, using a smart safety pin. More specifically, but not exclusively, disclosed are detonation control systems and methods, which include a detonation controller unit, a safety pin configured to engage with a safety pin holder of the detonation unit, and a remote controller unit configured to receive the safety pin, wherein, only when the safety pin is removed from the detonation controller unit and engaged with a remote controller unit, the remote controller unit is paired with the detonation controller unit and capable of communicating therewith.

Abstract: Provided herein are systems and methods for pairing a remote controller unit and a control unit, using a smart safety pin. More specifically, but not exclusively, disclosed are detonation control systems and methods, which include a detonation controller unit, a safety pin configured to engage with a safety pin holder of the detonation unit, and a remote controller unit configured to receive the safety pin, wherein, only when the safety pin is removed from the detonation controller unit and engaged with a remote controller unit, the remote controller unit is paired with the detonation controller unit and capable of communicating therewith.

Abstract: Apparatus and methods are described for use with electrophysiological signal detecting electrodes, and a transcranial magnetic stimulation device. A computer processor drives the transcranial stimulation device to apply one or more pulses of transcranial magnetic stimulation to a subject. Within a given time period of applying one of the one or more pulses of transcranial magnetic stimulation to the subject, the computer processor detects an electrophysiological signal of the subject, using the electrophysiological signal detecting electrodes. At least partially in response thereto, the computer processor predicts an outcome of treating the subject for a neuropsychiatric condition, using a given therapy, and generates an output on an output device in response to the predicted outcome. Other applications are also described.

Abstract: Apparatuses, methods and storage media associated with an environment recognition system using SLAM pipeline with semantic segmentation are described herein. In some instances, the system is mounted on the body of the robotic apparatus, and includes one or more light sources, to illuminate a portion of an environment that surrounds the apparatus; a camera, to capture one or more images of the illuminated portion of the environment; and a processing device coupled with the camera and the light sources, to process the captured images, using semantic segmentation of the images applied in a SLAM pipeline. The processing is used to identify a position of the body of the apparatus, and/or a position of one or more objects disposed in the illuminated portion of the environment, based at least in part on a result of the processing of the one or more images. Other embodiments may be described and claimed.

Abstract: A method comprising using at least one hardware processor for: providing a set of development supervectors representing features of biometric samples of multiple subjects, the biometric samples being of at least a first and a second different biometric modalities; providing at least a first and a second enrollment supervectors representing features of at least a first and a second enrollment biometric samples of a target subject correspondingly, wherein the at least first and second enrollment samples are of the at least first and the second different biometric modalities correspondingly; providing at least a first and a second verification supervectors representing features of at least a first and a second verification biometric samples of the target subject correspondingly, wherein the at least first and second verification samples are of the at least first and second different biometric modalities correspondingly; concatenating the development supervectors to a set of development generic supervector, the a

Abstract: Apparatus and methods are described for use with electrophysiological signal detecting electrodes, and a transcranial magnetic stimulation device. A computer processor drives the transcranial stimulation device to apply one or more pulses of transcranial magnetic stimulation to a subject. Within a given time period of applying one of the one or more pulses of transcranial magnetic stimulation to the subject, the computer processor detects an electrophysiological signal of the subject, using the electrophysiological signal detecting electrodes. At least partially in response thereto, the computer processor predicts an outcome of treating the subject for a neuropsychiatric condition, using a given therapy, and generates an output on an output device in response to the predicted outcome. Other applications are also described.

Abstract: Among the techniques described herein is a method that includes obtaining data indicating electrocardiogram results from a human. A plurality of beats represented in the electrocardiogram results can be identified. For each beat in the plurality of beats represented in the electrocardiogram results, a value for a first feature of the beat can be determined. Statistical analysis can be performed on the values for the first feature of the plurality of beats. An indication of the level of the analyte within the human can be generated based on a result of the statistical analysis performed on the values for the first feature of the plurality of beats. The indication of the level of the analyte within the human can be provided.

Abstract: A computer-implemented method for automating interaction with a computer system includes linking a control computer system to an input interface and to an output interface of a client computer system, which is operative for producing user interface images on a display device. The control computer system executes distinct software modules that include a virtual operator for simulating actions of a human operator. Execution of the software modules causes the control computer system to capture an image from the output interface, and to recognize information in the image. In response to the information, the virtual operator controls an input device to automatically execute predetermined operations on the client computer system via the input interface.

Abstract: A method includes identifying, in an image, a shelf, a price tag affixed to the shelf, a first group of one or more first products resting on the shelf and positioned on a first side of the price tag, and a second group of one or more second products resting on the shelf and positioned on a second side of the price tag. One or more first candidates are identified for the one or more first products, and one or more second candidates are identified for the one or more second products. Upon receiving information indicating expected locations for the first and the second candidates, determining, an identity of the first products can be determined based on the expected locations and the one or more first candidates, and an identity of second products can be determined based on the expected locations and the one or more second candidates.

Abstract: Systems and methods for extracting text from images rendered on a display screen, the method comprising capturing a color image rendered on a display screen; and transforming the color image to binary color image, preserving text-like graphic components and filtering out non-text-like graphical components. The transforming comprises scanning one or more areas of the color image; and detecting continuous bi-tonal regions in the scanned one or more areas, wherein the continuous bi-tonal regions have large variances.

Abstract: Machines, systems and methods for recognizing visual change in a graphical user interface (GUI) environment, the method comprising determining position of an active GUI object in the GUI environment based on known attributes of the active GUI object; monitoring a focus area in the active GUI object to detect visual changes in attributes of the focus area, without regard to any visual changes outside the focus area; determining whether the active GUI object has moved or has been resized, in response to determining a visual change in the attributes of the focus area; and determining position of a new active GUI object in the GUI environment, in response to determining that the active GUI object has not been moved or has not been resized.

Abstract: Systems and methods for extracting text from images rendered on a display screen, the method comprising capturing a color image rendered on a display screen; and transforming the color image to binary color image, preserving text-like graphic components and filtering out non-text-like graphical components. The transforming comprises scanning one or more areas of the color image; and detecting continuous bi-tonal regions in the scanned one or more areas, wherein the continuous bi-tonal regions have large variances.

Abstract: Systems and methods for extracting text from images rendered on a display screen, the method comprising capturing a color image rendered on a display screen; and transforming the color image to binary color image, preserving text-like graphic components and filtering out non-text-like graphical components. The transforming comprises scanning one or more areas of the color image; and detecting continuous bi-tonal regions in the scanned one or more areas, wherein the continuous bi-tonal regions have large variances.

Abstract: A method includes identifying, in an image, a shelf, a price tag affixed to the shelf, a first group of one or more first products resting on the shelf and positioned on a first side of the price tag, and a second group of one or more second products resting on the shelf and positioned on a second side of the price tag. One or more first candidates are identified for the one or more first products, and one or more second candidates are identified for the one or more second products. Upon receiving information indicating expected locations for the first and the second candidates, determining, an identity of the first products can be determined based on the expected locations and the one or more first candidates, and an identity of second products can be determined based on the expected locations and the one or more second candidates.

Abstract: A method includes identifying, in an image, a shelf, a price tag affixed to the shelf, a first group of one or more first products resting on the shelf and positioned on a first side of the price tag, and a second group of one or more second products resting on the shelf and positioned on a second side of the price tag. One or more first candidates are identified for the one or more first products, and one or more second candidates are identified for the one or more second products. Upon receiving information indicating expected locations for the first and the second candidates, determining, an identity of the first products can be determined based on the expected locations and the one or more first candidates, and an identity of second products can be determined based on the expected locations and the one or more second candidates.

Abstract: This document describes, among other things, a computer-implemented method that includes accessing, by a computer system, electrogram data for a patient, wherein the electrogram data is obtained using one or more leads that sense physiological electrical activity of the patient. The computer system can identify one or more waveform features from the electrogram data, and one or more correlations between values of the one or more waveform features and analyte levels. One or more estimated analyte levels in the patient are determined based on 1) the one or more waveform features identified from the electrogram data and 2) the one or more correlations. The computer system can output information related to the one or more estimated analyte levels.

Abstract: A method comprising using at least one hardware processor for: providing a set of development supervectors representing features of biometric samples of multiple subjects, the biometric samples being of at least a first and a second different biometric modalities; providing at least a first and a second enrollment supervectors representing features of at least a first and a second enrollment biometric samples of a target subject correspondingly, wherein the at least first and second enrollment samples are of the at least first and the second different biometric modalities correspondingly; providing at least a first and a second verification supervectors representing features of at least a first and a second verification biometric samples of the target subject correspondingly, wherein the at least first and second verification samples are of the at least first and second different biometric modalities correspondingly; concatenating the development supervectors to a set of development generic supervector, the a

Abstract: A method comprising using at least one hardware processor for: providing a set of development supervectors representing features of biometric samples of multiple subjects, the biometric samples being of at least a first and a second different biometric modalities; providing at least a first and a second enrollment supervectors representing features of at least a first and a second enrollment biometric samples of a target subject correspondingly; wherein the at least first and second enrollment samples are of the at least first and the second different biometric modalities correspondingly; providing at least a first and a second verification supervectors representing features of at least a first and a second verification biometric samples of the target subject correspondingly, wherein the at least first and second verification samples are of the at least first and second different biometric modalities correspondingly; concatenating the development supervectors to a set of development generic supervector, the a

Abstract: A method includes identifying, in an image, a shelf, a price tag affixed to the shelf, a first group of one or more first products resting on the shelf and positioned on a first side of the price tag, and a second group of one or more second products resting on the shelf and positioned on a second side of the price tag. One or more first candidates are identified for the one or more first products, and one or more second candidates are identified for the one or more second products. Upon receiving information indicating expected locations for the first and the second candidates, determining, an identity of the first products can be determined based on the expected locations and the one or more first candidates, and an identity of second products can be determined based on the expected locations and the one or more second candidates.

Abstract: Described are devices for automated ballistic targeting that are attached to a rifle for firing ballistic ammunition, in which such rifle may have one or more barrels for use with one or more types of ammunition. Various embodiments use one or more mirrors and an optical splitter all of which may be position-fixed or adjustable, a collimator sub-system, a data input unit, and a ballistic computer, in which the elements are configured to provide a calculated ballistic trajectory to hit a target, to correct elevation and azimuth, and to generate an aiming point that is super-imposed visually on an image of the target when the rifle is correctly aimed to hit the target (even where the ballistic trajectory requires that the aim be on an elevation or an azimuth off the target). In various embodiments, errors in roll maybe indicated and corrected. In various embodiments, periscope functionality may be used.