公开(公告)号：WO2023057224A1

公开(公告)日：2023-04-13

申请号：PCT/EP2022/076363

申请日：2022-09-22

Applicant: FOTONATION LIMITED

Inventor： TOPOLEANU, Tudor ,  FULOP, Szabolcs ,  BIGIOI, Petronel ,  RYAN, Cian ,  LEMLEY, Joseph

IPC: G06V10/82 ,  G06V40/20 ,  G06F18/2431 ,  G06F3/017 ,  G06V10/25 ,  G06V20/593 ,  G06V40/107 ,  G06V40/28

Abstract: A method for identifying a gesture from one of a plurality of dynamic gestures, each dynamic gesture comprising a distinct movement made by a user over a period of time within a field of view of an image acquisition device comprises iteratively: acquiring a current image from said image acquisition device at a given time; and passing at least a portion of the current image through a bidirectionally recurrent multi-layer classifier. A final layer of the multi-layer classifier comprises an output indicating a probability that a gesture from the plurality of dynamic gestures is being made by a user during the time of acquiring the image.

公开(公告)号：WO2022272311A1

公开(公告)日：2022-12-29

申请号：PCT/US2022/073173

申请日：2022-06-25

Applicant: QUALCOMM INCORPORATED

Inventor： BORSE, Shubhankar Mangesh ,  CAI, Hong ,  ZHANG, Yizhe ,  PORIKLI, Fatih Murat

IPC: G06N3/04 ,  G06N3/08 ,  G06F18/23 ,  G06F18/2431 ,  G06N3/045 ,  G06N3/082

Abstract: Certain aspects of the present disclosure provide techniques for training neural networks using hierarchical supervision. An example method generally includes training a neural network with a plurality of stages using a training data set and an initial number of classification clusters into which data in the training data set can be classified. A cluster-validation set performance metric is generated for each stage based on a reduced number of classification clusters relative to the initial number of classification clusters and a validation data set. A number of classification clusters to implement at each stage is selected based on the cluster-validation set performance metric and an angle selected relative to the cluster-validation set performance metric for a last stage of the neural network. The neural network is retrained based on the training data set and the selected number of classification clusters for each stage, and the trained neural network is deployed.

公开(公告)号：WO2022240404A1

公开(公告)日：2022-11-17

申请号：PCT/US2021/031991

申请日：2021-05-12

Applicant: GENESYS CLOUD SERVICES, INC.

Inventor： MAZZA, Arnon ,  HAIKIN, Lev ,  ORBACH, Eyal ,  FAIZAKOF, Avraham

IPC: G06F40/30 ,  G06F18/2113 ,  G06F18/217 ,  G06F18/241 ,  G06F18/2431 ,  G06F18/40 ,  G06N20/20

Abstract: A method and system for finetuning automated sentiment classification by at least one processor may include: receiving a first machine learning (ML) model M0, pretrained to perform automated sentiment classification of utterances, based on a first annotated training dataset; associating one or more instances of model M0 to one or more corresponding sites; and for one or more (e.g., each) ML model M0 instance and/or site: receiving at least one utterance via the corresponding site; obtaining at least one data element of annotated feedback, corresponding to the at least one utterance; retraining the ML model M0, to produce a second ML model M1, based on a second annotated training dataset, wherein the second annotated training dataset may include the first annotated training dataset and the at least one annotated feedback data element; and using the second ML model M1, to classify utterances according to one or more sentiment classes.

公开(公告)号：WO2023080975A1

公开(公告)日：2023-05-11

申请号：PCT/US2022/045559

申请日：2022-10-03

Applicant: ZENDRIVE, INC.

Inventor： CHANDRA, Sakshi ,  BHATTACHARYA, Sambuddha ,  PAL, Jayanta Kumar

IPC: G06F18/2431 ,  H04W4/38 ,  B60W40/10 ,  G06F18/27

Abstract: The system can include a plurality of data processing modules, which can include: a feature generation module, a scoring module, an optional decision module, an optional trip detection module, and/or any other suitable data processing modules. The system can optionally include a mobile device (e.g., such as a mobile cellular telephone, user device, etc.) and/or can be used in conjunction with a mobile device (e.g., receive data from an application executing at the mobile device and/or utilize mobile device processing, etc.). The system can function to classify a vehicular transportation modality (e.g., motorcycle transportation) for a vehicle trip.