Orbotech Limited

Nexar, Ltd.

Shmuel Rippa

Zeev Smilansky

Tally Gilat-Bernshtein

Eyal Klingbell

Sharon Duvdevani

Meir Mayo

Eliahu Brosh

Lev Yitzhak Lavy

Eran Shir

Ilan Kadar

Oren Meiri

Bruno Fernandez-Ruiz

Elad Levi

Roi Adadi

Roei Herzig

A system for training simultaneous localization and mapping (SLAM) models, including a camera, mounted in a vehicle and in communication with an image server via a cellular connection, that captures images labeled with a geographic position system location and a timestamp, and uploads them to an image server, a storage device that stores geographical maps and images, and indexes the images geographically with reference to the geographical maps, an images server that receives uploaded images, labels the uploaded images with a GPS location and a timestamp, and stores the uploaded images on the storage device, and a training server that trains a SLAM model using images labeled with a GPS location and a timestamp, wherein the SLAM model (i) receives an image as input and predicts the image location as output, and/or (ii) receives an image having error as input and predicts a local correction for the image as output.

Localization and mapping methods using vast imagery and sensory data collected from land and air vehicles

A networked system for providing public space data on demand, including a plurality of vehicles driving on city and state roads, each vehicle including an edge device with processing capability that captures frames of its vicinity, a vehicle-to-vehicle network to which the plurality of vehicle are connected, receiving queries for specific types of frame data, propagating the queries to the plurality of vehicles, receiving replies to the queries from a portion of the plurality of vehicles, and delivering matched data by storing the matched data into a centralized storage server, and a learner digitizing the public space in accordance with the received replies to the queries.

Digitizing and mapping the public space using collaborative networks of mobile agents and cloud nodes

An electrical circuit inspection method including, for each of a plurality of types of local characteristics, each type occurring at least once within electrical circuitry to be inspected, identifying at least one portion of interest within the electrical circuitry whereat the local characteristic is expected to occur, and inspecting an image of each portion of interest, using an inspection task selected in response to the type of local characteristic expected to occur in the portion of interest.

Apparatus and methods for the inspection of objects

A method for inspecting objects comprising: creating a reference image for a representative object, the reference image comprising an at least partially vectorized first representation of boundaries representing the representative object; acquiring an image of an object under inspection comprising a second representation of boundaries representing the object under inspection; and comparing a location of at least some boundaries in the second representation of boundaries to a location of corresponding boundaries in the at least partially vectorized first representation of boundaries, thereby to identify defects.

A method for inspecting electrical circuits, and a system for carrying out the method, generating a representation of boundaries of elements in an image of an electrical circuit which is under inspection, and analyzing at least some locations of at least some boundaries in the representation of boundaries of elements to identify defects in the electrical circuit.

Growing community of inventors

Ramat Gan, Israel

Shmuel Rippa