International Business Machines Corporation

Florian Pinel

Donna Karen Byron

Carmine M DiMascio

Benjamin L Johnson

Timothy P Winkler

Russell Patrick Bobbitt

Carmine Dimascio

Larisa Shwartz

Edward Eugene Seabolt

Lav Raj Varshney

David Matthew Loewenstern

Shikhar Kwatra

Melissa J Buco

Fenno F Heath, Iii

Robert N Redmond

Krishna Chaitanya Ratakonda

Pankaj Dhoolia

Rong Liu

Peter Alan Coldicott

Tova Roth

Mark Holmes Linehan

Santhosh Babu Kumaran

Christian Ewen

William S Spann, Iii

Nan Shao

Sarbajit Kumar Rakshit

Corville O Allen

Jana Helton Jenkins

Sushain Pandit

Yun Zhai

Shao Chun Li

Jie Cui

Jacquelyn Annette Martino

Paul N Krystek

Kush Raj Varshney

Yixin Diao

Maira Athanazio De Cerqueira Gatti

Ricardo Guimaraes Herrmann

Prabir Nandi

Frank Yeh, Jr

Brian Hull

Domenic A Venuto

Dashun Wang

Sharon Laquinta Cham

Jeremy R Fox

Vittorio R Castelli

Mauro Marzorati

Xin Zhou

Charles Evan Beller

Biplav Srivastava

Pawan Raghunath Chowdhary

Charles Daniel Wolfson

Alexander Pikovsky

Anne Elizabeth Gattiker

Chiao-Fe Shu

Mary Swift

Shyh-Kwei Chen

Frederick Y Wu

Richard Baxter Hull

Arjun Natarajan

Brent P Gross

Anil Nigam

Debarun Bhattacharjya

Sreeram Ramakrishnan

Mayoore Selvarasa Jaiswal

Tian J Chao

Themistoklis Palpanas

Ambal Balakrishnan

Ketan Barve

Christie Ewen

Matthew Comer

Carmine Michael Dimascio

Will Spann

Liang Tang

Richard Zhihuai Xue

Provided is a method, computer program product, and system for predicting image sharing decisions using machine learning. A processor may receive a set of annotated images and an associated text input from each user of a plurality of users. The processor may train, using the set of annotated images and the associated text input from each user, a neural network model to output an image sharing decision that is specific to a user.

Image dispositioning using machine learning

A method, computer system, and computer program product for determining a desirability of a product attribute are provided. The embodiment may include extracting a plurality of product features corresponding to one or more products. The embodiment may also include analyzing a plurality of product reviews to determine a sentiment toward the extracted product features. The embodiment may further include calculating a desirability score for each product feature. The embodiment may also include, in response to receiving a user query associated with a product, identifying a product feature to which the received user query relates. The embodiment may further include generating a response to the received user query based on the calculated desirability score.

Desirability of product attributes

Embodiments for managing personal device security by one or more processors are described. Information associated with activity of a personal device is received. The information is detected utilizing a sensor coupled to the personal device. A signal representative of the received information is generated. An operational state of the personal device is caused to be changed after the generating of the signal.

Methods and systems for managing personal device security

A method of calibrating a system including a camera, the method including detecting a robot navigating within an environment modeled as a geo-polygon space, including a transit of the robot through a scene of the environment captured by the camera, mapping a plurality of points occupied by the robot in images of the scene to the geo-polygon space, recording data about the mapping, and configuring at least one alert using the data recorded about the mapping, the alert executed by the computing system and configured to be triggered by an object transiting the scene.

Robotic geometric camera calibration and monitoring alert configuration and testing

A system and associated method may utilize a processor that receives recall product instance group (RPIG) information (RPIGI) identifying a set of instances of products having a product type identifier (PTI) that are a subject of a product recall. The processor receives, from an imaging device associated with a user, an image containing a product instance. The method further comprises applying a classifier and determining a PTI. Based on the image, secondary product information is also identified. These may be compared with the RPIGI to determine a product instance membership. Information related to the product instance membership in the RPIG may be displayed.

Targeted alerts for food product recalls

Aspects of this disclosure relate to a system that uses images of a load handled by a crane as captured by cameras to monitor the load. The images may include different sets of outer perimeters of the load. The system may identify the outer perimeters and then define a safety zone that extends beyond these outer perimeters. In response to identifying an object within the safety zone, the system may execute a remedial action.

Camera-assisted crane safety

A method, system, and computer program product for automated collection of training data and training object detection models is provided. The method generates a set of reference images for a first set of products. Based on the set of reference images, the method identifies a subset of products within an image stream. Based on the subset of products, a second set of products is determined within the image stream. The method identifies a set of product gaps based on the subset of products and the second set of products. The method generates a product detection model based on the set of reference images, the subset of products, the second set of products, and the product gaps.

Automated training data collection for object detection

A computer-implemented method for generating personalized image filters is disclosed. The computer-implemented method includes receiving a user request to generate a filter for an input image. The computer-implemented method further includes generating one or more keyword lists associated with the input image. The computer-implemented method further includes determining one or more themes associated with the input image based, at least in part, on one or more keywords selected from the one or more keyword lists. The computer-implemented method further includes identifying one or more candidate images matching the one or more themes associated with the image. The computer-implemented method further includes generating one or more personalized image filters based on one or more features from one or more of the candidate images.

Personalized multimedia filter

Embodiments of the present invention disclose a method, a computer program product, and a computer system predicting parking availability. A computer identifies parking spaces and groups the parking spacing into parking locations. In addition, the computer distinguishes private parking spaces from public parking spaces, and trains a crowd forecast model for each of the parking locations. The computer further receives a destination and preferences, from which the computer creates a geofence based on the destination and preferences. The computer then predicts parking availability based on the crowd forecast models and refines the crowd forecast model.

Parking availability predictor

A method includes receiving, by a first device of a transportation provider, a device ID of a particular device of a user and purchase information regarding a purchase, by the user, of one or more goods or services. The method includes sending, by the first device, the device ID of the particular user device to a central server. The method includes receiving, by the first device from the central server, information regarding the particular user device. The method includes determining, by the first device, a selected transportation vehicle based on the purchase information and the information regarding the particular user device. The method includes sending, by the first device, a vehicle ID of the selected transportation vehicle to the central server. The method includes providing a transportation service to the user using the particular user device and the selected transportation vehicle.

Devices, systems, and methods for secure and adaptable transportation of goods and/or persons

A method, computer system, and a computer program product for generating a custom object is provided. The present invention may include extracting a plurality of constituent components from a static list of previously determined objects associated with a place of purchase. The present invention may then include receiving, from a user, one or more custom objects based on the extracted plurality of constituent components from the place of purchase. The present invention may also include generating, dynamically, a price for each of the one or more selected custom objects based on the extracted plurality of constituent components. The present invention may further include presenting, to the user, the selected one or more custom objects.

Creating custom objects from a static list of objects and turning the custom objects into trends

Selectively redacting an image by determining a set of attributes used by a machine learning model for an analysis, receiving image data detecting, by the one or more computer processors, a portion of the image data relevant to the analysis, the portion comprising at least some of the set of attributes, generating a synthetic portion from the portion, wherein the synthetic portion retains at least some of the attributes of the detected portion, replacing the portion with the synthetic portion, yielding redacted image data, and providing the redacted image data for analysis.

Selective redaction of images

Embodiments relate to a system, program product, and method for use with an intelligent computer platform and cognitive processing and associated distribution. The embodiments support a mechanism for dynamically sharing critical and non-critical information responsive to a classification model, such that only relevant information or part of the information is shared. As the classification model is subject to modification, the dynamic sharing mechanism is dynamically updated to reflect such modification. Similarly, as an associated document or file is subject to modification, dynamic processing of the document or file takes place responsive to the classification model. The dynamic classification and document processing employ NLP and ML models to support the associated functionality.

Cognitive hierarchical content distribution

According to one embodiment, a method, computer system, and computer program product for navigating driverless vehicles is provided. The present invention may include ingesting data pertaining to the operation of the driverless vehicle, utilizing that data to predict tasks, which are driverless vehicle service tasks such as parking, maintenance, fueling, et cetera. The invention may further include determining the risk that a user may have need of the driverless vehicle, and scheduling the tasks to provide a balanced combination of convenience to the user, effective maintenance of the driverless vehicle, cost, and time. The method further includes navigating the driverless vehicle to accomplish the scheduled tasks.

Navigation via predictive task scheduling interruption for autonomous vehicles

Growing community of inventors

New York, NY, United States of America

Florian Pinel