Abstract: A method of self-localizing with respect to surrounding objects, comprising obtaining an approximated geolocation of the vehicle, retrieving mapping data comprising a geolocation of one or more stationary objects located in an area surrounding the approximated geolocation, receiving imagery data of a surrounding environment of the vehicle captured by a plurality of distinct imaging sensors deployed in the vehicle, applying one or more trained machine learning models to identify one or more of the stationary objects in the imagery data, computing a relative positioning of the vehicle with respect to one or more of the stationary objects based on an orientation of each of the plurality of imaging sensors with respect to the stationary object(s), computing an absolute positioning of the vehicle based on the relative positioning and the geolocation of the stationary object(s), and outputting the vehicle's absolute positioning.

Abstract: Disclosed herein are methods and systems for encoding data in composite patterns such that the encoded data is perceptible in one or more infrared spectral ranges while significantly imperceptible in visible light spectral range by encoding the data in one or more first partial patterns and/or in one or more second partial patterns of the composite pattern where the first partial pattern(s) is painted using a first print material and the second partial pattern(s) is painted using a second. The first and second paint materials are characterized by reflecting substantially similar light in the visible light spectral range and significantly different light in the infrared spectral range(s) such that the first and second patterns are indistinguishable in the visible light spectral range while highly distinguishable in the infrared spectral range(s). further disclosed are methods and systems for decoding the composite patterns to decode and extract the encoded data.

Abstract: There is provided a system of cryptography for securing data on a blockchain, comprising: at least one hardware processor executing a code for: obtaining at least one encrypted data item, encrypted with a public key compliant with a homomorphic encryption mechanism, feeding the at least one encrypted data item into a computational process that computationally processes the at least one encrypted data item with computations compliant with the homomorphic encryption mechanism, and providing at least one encrypted outcome of the computational process to a smart contract for posting on a blockchain, wherein the at least one encrypted outcome is compliant with the homomorphic encryption mechanism and decrypted with a private key corresponding to the public key.

Abstract: There is provided a computed implemented method of automatically generating an adapted presentation of at least one candidate anomalous object detected from anatomical imaging data of a target individual, comprising: providing anatomical imaging data of the target individual acquired by an anatomical imaging device, analyzing the anatomical imaging data by a detection classifier for detecting at least one candidate anomalous object of the anatomical imaging data and computed associated location thereof, computing, by a presentation parameter classifier, at least one presentation parameter for adapting a presentation of a sub-set of the anatomical imaging data including the at least one candidate anomalous object according to at least the location of the candidate anomalous object, and generating according to the at least one presentation parameter, an adapted presentation of the sub-set of the anatomical imaging data including the at least one candidate anomalous object.

Abstract: There is provided a system for measuring a physiological parameter of a person indicative of physiological pathology, comprising: a plurality of remote non-contact sensors, each of a different type of sensing modality, at least one hardware processor executing a code for: simultaneously receiving over a time interval, from each of the plurality of remote non-contact sensors monitoring a person, a respective dataset, extracting, from each respective dataset, a respective sub-physiological parameter of a plurality of sub-physiological parameters, analyzing a combination of the plurality of sub-physiological parameters, and computing a physiological parameter indicative of physiological pathology according to the analysis, wherein an accuracy of the physiological parameter computed from the combination is higher than an accuracy of the physiological parameter independently computed using any one of the plurality of sub-physiological parameters.

Abstract: Disclosed herein are methods and systems for determining liveness of a user, comprising analyzing visual content of a screen of a client device used by a user to access an online service, adjusting one or more visual objects displayed on the screen of the client device according to dynamically changing patterns, capturing a sequence of images depicting one or more reflecting surfaces associated with the user viewing the screen while the visual objects are displayed, analyzing the images to identify a reflection of the displayed visual objects in the reflecting surfaces and verifying liveness of the user based on one or more of a plurality of reflection attributes of the identified reflection.

Abstract: There is provided a computer implemented method of computing a location of an object, comprising: accessing a wide field of view (wFOV) image captured by a wFOV image sensor located relative to an object, analyzing the wFOV image to identify a predefined feature, wherein the predefined feature indicates a low accuracy location of the object, capturing a high resolution image by a high resolution image sensor located relative to the object, the high resolution image depicting the predefined feature, and computing a high accuracy of location of the object according to an analysis of the predefined feature and according to a correlation between a location and orientation of the wFOV image sensor and the high resolution image sensor.

Abstract: Disclosed herein are methods and systems for determining whether a user engaged in an interactive video session is a genuine user or a potential impersonator by analyzing a plurality of consecutive images depicting the user while engaged in the video session to identify one or more dynamic facial patterns in the face of the user while his lips are moving. Each such dynamic facial pattern may express a movement of one or more of a plurality of wrinkles and/or other dynamic facial features (e.g., nostrils, distance between nostrils, ear, skin portion, muscle, etc.) in the face of the user. The user may be then determined to be genuine or not based on a comparison between the identified dynamic facial pattern(s) and one or more reference dynamic facial patterns.

Abstract: A system for detecting malicious software, comprising at least one hardware processor adapted to: execute a tested software object in a plurality of computing environments each configured according to a different hardware and software configuration; monitor a plurality of computer actions performed in each of the plurality of computing environments when executing the tested software object; identify at least one difference between the plurality of computer actions performed in a first of the plurality of computing environments and the plurality of computer actions performed in a second of the plurality of computing environments; and instruct a presentation of an indication of the identified at least one difference on a hardware presentation unit.

Abstract: There is provided a method of re-classifying a clinically significant feature of a medical image as an artifact, comprising: feeding a target medical image captured by a specific medical imaging sensor at a specific setup into a machine learning model, obtaining a target feature map as an outcome of the machine learning model, wherein the target feature map includes target features classified as clinically significant, analyzing the target feature map with respect to sample feature map(s) obtained as an outcome of the machine learning model fed a sample medical image captured by at least one of: the same specific medical imaging sensor and the same specific setup, wherein the sample feature map(s) includes sample features classified as clinically significant, identifying target feature(s) depicted in the target feature map having attributes matching sample feature(s) depicted in the sample feature map(s), and re-classifying the identified target feature(s) as an artifact.

Abstract: Disclosed herein are methods and systems for determining liveness of a user, comprising analyzing visual content of a screen of a client device used by a user to access an online service, adjusting one or more visual objects displayed on the screen of the client device according to dynamically changing patterns, capturing a sequence of images depicting one or more reflecting surfaces associated with the user viewing the screen while the visual objects are displayed, analyzing the images to identify a reflection of the displayed visual objects in the reflecting surfaces and verifying liveness of the user based on one or more of a plurality of reflection attributes of the identified reflection.

Abstract: There is provided a computer implemented method of measuring a temperature of a subject, comprising: receiving a sequence of a plurality of thermal images of a subject captured by a thermal sensor, analyzing the sequence of the plurality of thermal images to identify at least one target thermal image depicting an upper region of a tongue of the subject, analyzing the at least one target thermal image to identify an estimated temperature of the upper region of the tongue, and providing the estimated temperature of the upper region of the tongue.

Abstract: An automated health check device and methods, the device comprising: at least one imaging sensor configured for capturing at least one image of at least an area confined by a window of the vehicle; at least one vital signs sensor configured for measuring a health parameter of a passenger at the area confined by the window; and at least one processor configured for: acquiring and analyzing the at least one image to determine location of the window; determining based on the determined location of the window a location of the passenger; determining the at least one vital signs sensor being oriented to a predetermined point of view in relation to the location of the passenger determined; and obtaining a measurement of the health parameter of the passenger from the at least one vital signs sensor.

Abstract: Disclosed herein are methods and systems for encoding data in composite patterns such that the encoded data is perceptible in one or more infrared spectral ranges while significantly imperceptible in visible light spectral range by encoding the data in one or more first partial patterns and/or in one or more second partial patterns of the composite pattern where the first partial pattern(s) is painted using a first print material and the second partial pattern(s) is painted using a second. The first and second paint materials are characterized by reflecting substantially similar light in the visible light spectral range and significantly different light in the infrared spectral range(s) such that the first and second patterns are indistinguishable in the visible light spectral range while highly distinguishable in the infrared spectral range(s). further disclosed are methods and systems for decoding the composite patterns to decode and extract the encoded data.

Abstract: Disclosed herein are methods and systems for encoding data in composite patterns such that the encoded data is perceptible in one or more infrared spectral ranges while significantly imperceptible in visible light spectral range by encoding the data in one or more first partial patterns and/or in one or more second partial patterns of the composite pattern where the first partial pattern(s) is painted using a first print material and the second partial pattern(s) is painted using a second. The first and second paint materials are characterized by reflecting substantially similar light in the visible light spectral range and significantly different light in the infrared spectral range(s) such that the first and second patterns are indistinguishable in the visible light spectral range while highly distinguishable in the infrared spectral range(s). further disclosed are methods and systems for decoding the composite patterns to decode and extract the encoded data.

Abstract: Disclosed herein are methods and systems for encoding data in composite patterns such that the encoded data is perceptible in one or more infrared spectral ranges while significantly imperceptible in visible light spectral range by encoding the data in one or more first partial patterns and/or in one or more second partial patterns of the composite pattern where the first partial pattern(s) is painted using a first print material and the second partial pattern(s) is painted using a second. The first and second paint materials are characterized by reflecting substantially similar light in the visible light spectral range and significantly different light in the infrared spectral range(s) such that the first and second patterns are indistinguishable in the visible light spectral range while highly distinguishable in the infrared spectral range(s). further disclosed are methods and systems for decoding the composite patterns to decode and extract the encoded data.

Abstract: Disclosed herein are methods and systems for determining liveness of a user, comprising analyzing visual content of a screen of a client device used by a user to access an online service, adjusting one or more visual objects displayed on the screen of the client device according to dynamically changing patterns, capturing a sequence of images depicting one or more reflecting surfaces associated with the user viewing the screen while the visual objects are displayed, analyzing the images to identify a reflection of the displayed visual objects in the reflecting surfaces and verifying liveness of the user based on one or more of a plurality of reflection attributes of the identified reflection.

Abstract: Methods and systems fort operating one or more light sources to project adversarial patterns generated to disorient a machine learning based detection system, comprising generating one or more adversarial patterns configured to disorient the machine learning based detection system and operating one or more light sources configured to project one or more of the adversarial pattern(s) in association with the targeted object in order to disorient the machine learning based detection system.

Abstract: Disclosed herein are methods and system for determining whether a user is wearing a mask, comprising receiving one or more infrared images depicting the user's face in one or more infrared spectral ranges and one or more visible light images depicting the user's face in visible light spectral range, registering the infrared image(s) to the visible light image(s), computing luminance values of a plurality of pixels relating to the user's face in the visible light image(s), computing infrared reflectiveness values of corresponding pixels in the registered infrared light image(s), computing, for each of the pixels, a difference between the luminance value and the infrared reflectiveness value and determining the user is genuine and not wearing a mask in case an aggregated difference aggregating the difference values of the pixels relating to the user's face exceeds a certain value.

Abstract: Disclosed herein are methods and system for determining whether a user is wearing a mask, comprising receiving one or more infrared images depicting the user's face in one or more infrared spectral ranges and one or more visible light images depicting the user's face in visible light spectral range, registering the infrared image(s) to the visible light image(s), computing luminance values of a plurality of pixels relating to the user's face in the visible light image(s), computing infrared reflectiveness values of corresponding pixels in the registered infrared light image(s), computing, for each of the pixels, a difference between the luminance value and the infrared reflectiveness value and determining the user is genuine and not wearing a mask in case an aggregated difference aggregating the difference values of the pixels relating to the user's face exceeds a certain value.