International Business Machines Corporation

Verily Life Sciences LLC

Amit Aides

Hagai Aronowitz

Yossi Matias

Ehud Benyamin Rivlin

Joseph Shtok

Leonid Karlinsky

Daniel Freedman

Amit Alfassy

Yacob Yochai Blau

Ilan Moshe Shimshoni

Liran Katzir

David Dov

The present disclosure is directed towards systems and methods that leverage machine-learned models to decrease the rate at which abnormal sites are missed during a gastroenterological procedure. In particular, the system and methods of the present disclosure can use machine-learning techniques to determine the coverage rate achieved during a gastroenterological procedure. Measuring the coverage rate of the gastroenterological procedure can allow medical professionals to be alerted when the coverage output is deficient and thus allow an additional coverage to be achieved and as a result increase in the detection rate for abnormal sites (e.g., adenoma, polyp, lesion, tumor, etc.) during the gastroenterological procedure.

Detecting deficient coverage in gastroenterological procedures

A system for generating a set of digital image features, comprising at least one hardware processor adapted for: producing a plurality of input groups of features, each produced by extracting a plurality of features from one of a plurality of digital images; computing an output group of features by inputting the plurality of input groups of features into at least one prediction model trained to produce a model group of features in response to at least two groups of features, such that a model set of labels indicative of the model group of features is similar, according to at least one similarity test, to a target set of labels computed by applying at least one set operator to a plurality of input sets of labels each indicative of one of the at least two groups of features; and providing the output group of features to at least one other processor.

Method and system for producing digital image features

Embodiments of the present systems and methods may provide techniques for handling acoustic-lips timing mismatch in audiovisual processing. In embodiments, the context-dependent time shift between the audio and visual streams may be explicitly modeled using an attention mechanism. For example, in an embodiment, a computer-implemented method for determining a context-dependent time shift of audio and video features in an audiovisual stream or file may comprise receiving audio information and video information of the audiovisual stream or file, processing the audio information and video information separately to generate a new representation of the audio information, including information relating to features of the audio information, and a new representation of the video information, including information relating to features of the video information, and mapping features of the audio information and features of the video information using an attention mechanism to identify synchronized pairs of audio and video features.

Attention mechanism for coping with acoustic-lips timing mismatch in audiovisual processing

Methods, computing systems and computer program products implement embodiments of the present invention that include receiving, at a first time, first video and first audio signals generated in response to a user uttering a passphrase, and receiving, at a second time subsequent to the first time, second video and second audio signals generated in response the user uttering the passphrase. Upon computing an audio temporal alignment between the first and the second audio signals and computing a video temporal alignment between the first and the second video signal, the user can be authenticated by comparing the audio temporal alignment to the video temporal alignment.

User authentication using audiovisual synchrony detection

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Haifa, Israel

Amit Aides