Abstract: Mobile handheld electronic devices such as smartphones, comprising a Wide camera for capturing Wide images with respective Wide fields of view (FOVW), a Tele camera for capturing Tele images with respective Tele fields of view (FOVT) smaller than FOVW, and a processor configured to stitch a plurality of Wide images into a panorama image with a field of view FOVP>FOVW and to pin a Tele image to a given location within the panorama image to obtain a smart panorama image.

Abstract: Techniques are disclosed relating to weakly supervised machine learning, which may be employed when there is a limited amount of labeled data available. A computer system may generate respective sets of synthetic labels for unlabeled data for a classification problem, where a given set of synthetic labels is produced by a corresponding one of a plurality of different label models. The computer system may then fit a set of supervised models, where each supervised model is fitted with one of the respective sets of synthetic labels to produce a respective set of predictions. The computer system may then evaluate the set of supervised models based on their respective set of predictions and using a set of labeled data for the classification problem. The evaluation may be used to select a particular supervised model and its corresponding label model.

Abstract: Disclosed herein are methods and systems for efficiently retrieving data from an at least partially encrypted table based record using secure Multi-Party Computation (MPC). A query received to retrieve data from a table based record comprising data items arranged in rows and columns may include a queried data item (key) which potentially matches one or more encrypted data items contained in one or more of the columns. The computing nodes, each having a respective one of a plurality of shares of a one-hot representation of each of the encrypted data items engage in the MPC session to match between a one-hot representation of the queried data item and the one-hot representation of each encrypted data item and output each matching row. The match is based on multiplying, in each encrypted data item's one-hot representation, only bits identified as hot in the queried data item's one-hot representation.

Abstract: There is provided a medical imaging processing device, comprising: at least one hardware processor executing a code for: iteratively generating instructions for iterative adjustment of presentation parameter(s) of a 2D frame of the 3D anatomical image presented on the display, for creating a sequence of adapted 2D frames of the 3D anatomical image, the instructions transmitted from the medical imaging processing device to a physical input interface of at least one of the client terminal and display, for each respective 2D frame: capturing the respective 2D frame from video signals transmitted from the client terminal to the display, analyzing the respective captured 2D frame for extraction of a 2D anatomical image, analyzing the respective captured 2D frame to identify metadata element(s), converting the metadata element(s) into converted metadata value(s), and formatting the extracted 2D anatomical images and associated converted metadata values for reconstruction of the 3D anatomical image.

Abstract: There is provided a medical imaging processing device, comprising: at least one hardware processor executing a code for: iteratively generating instructions for iterative adjustment of presentation parameter(s) of a 2D frame of the 3D anatomical image presented on the display, for creating a sequence of adapted 2D frames of the 3D anatomical image, the instructions transmitted from the medical imaging processing device to a physical input interface of at least one of the client terminal and display, for each respective 2D frame: capturing the respective 2D frame from video signals transmitted from the client terminal to the display, analyzing the respective captured 2D frame for extraction of a 2D anatomical image, analyzing the respective captured 2D frame to identify metadata element(s), converting the metadata element(s) into converted metadata value(s), and formatting the extracted 2D anatomical images and associated converted metadata values for reconstruction of the 3D anatomical image.

Abstract: There is provided a medical imaging processing device, comprising: at least one hardware processor executing a code for: iteratively generating instructions for iterative adjustment of presentation parameter(s) of a 2D frame of the 3D anatomical image presented on the display, for creating a sequence of adapted 2D frames of the 3D anatomical image, the instructions transmitted from the medical imaging processing device to a physical input interface of at least one of the client terminal and display, for each respective 2D frame: capturing the respective 2D frame from video signals transmitted from the client terminal to the display, analyzing the respective captured 2D frame for extraction of a 2D anatomical image, analyzing the respective captured 2D frame to identify metadata element(s), converting the metadata element(s) into converted metadata value(s), and formatting the extracted 2D anatomical images and associated converted metadata values for reconstruction of the 3D anatomical image.

Abstract: There is provided a medical imaging processing device, comprising: at least one hardware processor executing a code for: iteratively generating instructions for iterative adjustment of presentation parameter(s) of a 2D frame of the 3D anatomical image presented on the display, for creating a sequence of adapted 2D frames of the 3D anatomical image, the instructions transmitted from the medical imaging processing device to a physical input interface of at least one of the client terminal and display, for each respective 2D frame: capturing the respective 2D frame from video signals transmitted from the client terminal to the display, analyzing the respective captured 2D frame for extraction of a 2D anatomical image, analyzing the respective captured 2D frame to identify metadata element(s), converting the metadata element(s) into converted metadata value(s), and formatting the extracted 2D anatomical images and associated converted metadata values for reconstruction of the 3D anatomical image.

Abstract: In a method for inferring a topology of components in a network, at least one operation parameter is provided for each of a plurality of components in a network, and a similarity measure is computed between at least two of said components based on values of said operation parameters. Based on said similarity measure, it is determined whether said two components are topologically connected, wherein said similarity measure is computed in terms of a normalized mutual information between said operation parameters pertaining to said two components.

Abstract: Provided are chimeric antigen receptor (CAR) molecules comprising an extracellular domain comprising an antigen binding domain, a transmembrane domain, and an intracellular signaling domain, wherein an affinity of said binding domain to said antigen is characterized by a KD higher than 150 nM. Also provided are isolated polynucleotides and nucleic acid constructs comprising same, cells transduced with same and methods of using same.

Abstract: In a method for inferring a topology of components in a network. At least one operation parameter is provided for each of a plurality of components in a network, and a similarity measure is computed between at least two of said components based on values of said operation parameters. Based on said similarity measure, it is determined whether said two components are topological connected, wherein a said similarity measure is computed in terms of a normalized mutual information between said operation parameters pertaining to said two components.