Other

Technion Research & Development Foundation Limited

Intel Corporation

Ramot at Tel-aviv University Ltd.

Intel Benelux B.v.

Bronstein Bronstein Kimmel Technologies Ltd.

Alexander Bronstein

Michael Bronstein

Ron Kimmel

Shlomo Selim Rakib

Ofir Weber

Yohai Devir

Aviad Zabatani

Erez Sperling

Vitaly Surazhsky

Eliyahu Schwartz

Guy Rosman

Gilles Bruno Marie Devictor

Emanuel Marom

Abraham Mendelson

Ohad Menashe

Eitan Zeiler

Harel Haim

Asaf Matatyaou

Oleg Michailovich

Michael Zibulevsky

Grigoriy Zurakhov

Raja Giryes

Ortal Senouf

Chaim Baskin

Evgenii Zheltonozhskii

Sanketh Vedula

Natan Liss

A system for training a quantized neural network dataset, comprising at least one hardware processor adapted to: receive input data comprising a plurality of training input value sets and a plurality of target value sets; in each of a plurality of training iterations: for each layer, comprising a plurality of weight values, of one or more of a plurality of layers of a neural network: compute a set of transformed values by applying to a plurality of layer values one or more emulated non-uniformly quantized transformations by adding to each of the plurality of layer values one or more uniformly distributed random noise values; and compute a plurality of output values; compute a plurality of training output values; and update one or more of the plurality of weight values to decrease a value of a loss function; and output the updated plurality of weight values of the plurality of layers.

System and method for emulating quantization noise for a neural network

A method of processing an image is disclosed. The method comprises decomposing the image into a plurality of channels, each being characterized by a different depth-of-field, and accessing a computer readable medium storing an in-focus dictionary defined over a plurality of dictionary atoms, and an out-of-focus dictionary defined over a plurality of sets of dictionary atoms, each set corresponding to a different out-of-focus condition. The method also comprises computing one or more sparse representations of the decomposed image over the dictionaries.

Method and system for processing an image

There is provided an ultrasound device comprising: ultrasound transducer(s), memory storing code, hardware processor(s) coupled to the ultrasound transducer(s) and the memory for executing stored code comprising: activating the transducer(s) for simultaneously transmitting at least one line with a predefined focus width, and receiving an indication of a plurality of narrow-focused received lines, inputting the indication of the narrow-focused received lines into a convolutional neural network (CNN) trained on pairs of ultrasound imaging data capturing rapid motion of the certain tissue of sample patient(s), including a single-line ultrasound imaging data captured based on a single line in response to a transmitted single narrow-focused pulse, and a multiple-line ultrasound imaging data captured based on receiving narrow-focused lines in response to simultaneously transmitted at least one line, outputting adjusted narrow-focused received lines, and computing an adjusted ultrasound image according to the adjusted narrow-focused received lines for presentation on a display.

Systems and methods for ultrasonic imaging

A method of processing an input image comprises receiving the input image, storing the image in a memory, and accessing, by an image processor, a computer readable medium storing a trained deep learning network. A first part of the deep learning network has convolutional layers providing low-level features extracted from the input image, and convolutional layers providing a residual image. A second part of the deep learning network has convolutional layers for receiving the low-level features and extracting high-level features based on the low-level features. The method feeds the input image to the trained deep learning network, and applies a transformation to the residual image based on the extracted high-level features.

Method and system for end-to-end image processing

A method for planning a current medical procedure to be performed on a body part of a current patient includes obtaining a current first representation of a surface of the body part of the current patient, and either obtaining a representation of a desired result surface for the current medical procedure or selecting parameters for the current medical procedure. The method further includes retrieving at least one best matching record from a database of records of previously performed medical procedures of previous patients, based on a similarity criterion. Each record includes: parameters of a previously performed procedure of the previously performed medical procedures, a first representation of the body part of the previous patient prior to performance of the previously performed procedure, and a second representation of a body part of the previous patient after the performance of the previously performed procedure. The method further includes determining parameters of the current medical procedure based on the parameters of the retrieved record, or generating a representation of a predicted result for the current medical procedure on the body part of the current patient based on the retrieved record.

Surgery planning based on predicted results

In accordance with disclosed embodiments, there are provided systems, methods, and apparatuses for implementing maximum likelihood image binarization in a coded light range camera. For instance, a depth camera is described having therein a projector to project a collection of planes, each at a different angle of projection, onto a scene via a plurality of coded pattern images, each of the coded pattern images having encoded therein via a plurality of stripes, the angle of projection for the plane of projection within which the respective coded pattern image is projected; a detector to capture the plurality of coded pattern images from the scene; a processing component to adjust for ambient illumination and reflection properties of the scene; in which the processing component to further output a bit value for each pixel in the captured plurality of coded pattern images and to output a sub-pixel offset for the pixels positioned upon transitions of the plurality of stripes in the captured plurality of coded pattern images; a decoder to decode each of the plurality of coded pattern images and to adjust the decoded plurality of coded image patterns based on the sub-pixel offsets to determine the angle of projection for the corresponding plane of projection; and a triangulator to determine a position of an object in the scene based on an intersection of the determined angle of projection for the corresponding plane of projection with a known ray emanating from the detector that detected the plurality of the coded pattern images from the scene. Other related embodiments are disclosed.

Systems, methods, and apparatuses for implementing maximum likelihood image binarization in a coded light range camera

A method for multidimensional scaling (MDS) of a data set comprising a plurality of data elements is provided, wherein each data element is identified by its coordinates, the method comprising the steps of: (i) applying an iterative optimization technique, such as SMACOF, a predetermined amount of times on a coordinates vector, said coordinates vector representing the coordinates of a plurality of said data elements, and obtaining a modified coordinates vector; (ii) applying a vector extrapolation technique, such as Minimal Polynomial Extrapolation (MPE) or reduced Rank Extrapolation (RRE) on said modified coordinates vector obtaining a further modified coordinates vector; and (iii) repeating steps (i) and (ii) until one or more predefined conditions are met.

Acceleration of multidimensional scaling by vector extrapolation techniques

Various embodiments are generally directed to an apparatus, method, system, and/or other techniques to determine estimated ambient electromagnetic (EM) radiation information based at least partially on ambient recovery sensor measurement information, determine estimated albedo information based at least partially on albedo recovery sensor measurement information, albedo recovery emitter modulation information, sensing matrix information, and the estimated ambient EM radiation information, and determine estimated range information based at least partially on range recovery sensor measurement information, the estimated albedo information, range recovery emitter modulation information, and sensing matrix information.

Techniques for spatio-temporal compressed time of flight imaging

In accordance with disclosed embodiments, there are provided systems, methods, and apparatuses for implementing maximum likelihood image binarization in a coded light range camera. For instance, a depth camera is described having therein a projector to project a collection of planes, each at a different angle of projection, onto a scene via a plurality of coded pattern images, each of the coded pattern images having encoded therein via a plurality of stripes, the angle of projection for the plane of projection within which the respective coded pattern image is projected; a detector to capture the plurality of coded pattern images from the scene; a processing component to output a bit value for each pixel in the captured plurality of coded pattern images based on the pixel captured and based further on a patch of neighboring pixels surrounding the pixel; a decoder to decode each of the plurality of coded pattern images based on the bit values output by the processing component to determine the angle of projection for the corresponding plane of projection; and a triangulator to determine a position of an object in the scene based on an intersection of the determined angle of projection for the corresponding plane of projection with a geometric ray originating from the detector that detected the plurality of the coded pattern images. Other related embodiments are disclosed.

Method for parallel approximation of distance maps on a discrete representation of a manifold, the method comprising: for at least one Euclidean grid applied on the discrete representation of a manifold, iterating over rows of the Euclidean grid in a first direction, and for each row currently visited during the iterating in the first direction, calculating a distance value for each single cell of the currently visited row in parallel, wherein the calculating is carried out according to a predefined approximation rule, using a distance value calculated for each one of respective cells of a row visited immediately before the currently visited row, wherein the cells of the row visited before the currently visited row are adjacent to the single cell in the Euclidean grid.

Parallel approximation of distance maps

The present invention describes a system and method for controlling interactive video, including a remote control device allowing the user to interact with the video. The method allows bringing the 'lean-forward' hypervideo experience to a 'lay-back' environment such as the TV screen. The method also allows for the creation of a single system that combines both the social aspects of the &#x201c;lay-back&#x201d; and the &#x201c;lean-forward experience&#x201d; into a new type of rich media viewing experience.

Systems and methods for remote control of interactive video

The invention is directed to a system and method for determining position and orientation with respect to a display device. In particular, the invention is directed to acquiring an observed image from a display device using a pointing device, and calculating pointing device position and orientation using the acquired observed image and a displayed image on the display device.

System and method for user object selection in geographic relation to a video display

A universal video-related lookup system and method receives a request for information associated with specific video content from a requesting device. The system and method identify a first video content identifier associated with the specific video content and retrieves first metadata associated with the specific video content based on the first video content identifier. Next, the system and method translate the first video content identifier into a second video content identifier associated with the specific video content and retrieves second metadata based on the second video content identifier. The first metadata and the second metadata are then provided to the requesting device.

Universal lookup of video-related data

A method determines similarity of objects depicted in images when the images pertain to different modalities. The method includes obtaining images that depict the objects and that pertain to the different modalities. An embedding function is applied to each of the images. The embedding function is selected from a set of two or more embedding functions, each of the embedding functions corresponding to a modality of the different modalities, the selected embedding function corresponding to the modality of the image to which it is applied. Application of the embedding function maps that image to a representation in a representation space such that when the images are mapped to the representation space, a distance between the representations of the images is indicative of a similarity of their depicted objects. The similarity of the depicted objects is determined based on the location of the corresponding representations in the representation space.

Growing community of inventors

Haifa, Israel

Alexander Bronstein