International Business Machines Corporation

Petrogal Brasil S.a.

Andrea Britto Mattos Lima

Carlos Henrique Cardonha

Priscilla Barreira Avegliano

Vagner Figueredo De Santana

Marisa Affonso Vasconcelos

Vagner F D Santana

Rogerio Abreu De Paula

Rodrigo Laiola Guimaraes

Miguel Paredes Quinones

Maciel Zortea

Dario Augusto Borges Oliveira

Juliana De Melo Batista Dos Santos

Marco Aurelio Stelmar Netto

Lucas Correia Villa Real

Emilio Ashton Vital Brazil

Igor Cerqueira Oliveira

Renato Fontoura De Gusmão Cerqueira

Viviane Torres Da Silva

Rodrigo Da Silva Ferreira

Stefany Mazon

Vagner F De Santana

Joana De Noronha Ribeiro De Almeida

Matheus Palhares Viana

Maysa Malfiza Garcia De Macedo

Marco Daniel Melo Ferraz

Astrid De Jesus Torres Fernandez

Pablo Gonzalez

Dario Sergio Cersósimo

Allysson Flavio Melo De Oliveira

Diego Brito Veiga

Systems and methods for adapting physical activities and exercises based on facial analysis by image processing are disclosed. A method includes: identifying, by a computer device, a user; receiving, by the computer device, video data of a face region of the user while the user is engaged in exercise or physical activity; analyzing, by the computer device, the video data to determine a detected state of the user, wherein the analyzing the video data includes performing facial analysis using the video data; and providing, by the computer device, feedback to the user based on the analyzing the video data.

Adapting physical activities and exercises based on facial analysis by image processing

A system for providing permissioned images in media transactions is described. The system processes images in an image set for a media transaction to identify the image owner and other persons depicted in the image and determines use permissions for the images. Various images in the image set are processed to remove or anonymize various persons in order to meet use conditions. The processed images are compiled and provided to an entity requesting the image set.

Media transactions consent management

A computer completes a data image analysis task. The computer receives a machine learning (ML) model trained for use with image data content characterized by first context. The computer receives an evaluation image dataset having evaluation image data content characterized by a second context. The computer receives a request to complete an image data analysis task for the evaluation image dataset using the ML model. The computer compares the contexts to determine whether the contexts are similar and whether the evaluation image dataset is compatible with the ML model. If the evaluation dataset is incompatible with the ML model, the computer uses the generative model to generate a ML model compatible synthetic image dataset based on the evaluation dataset. The computer applies the ML model to the synthetic image dataset to provide an answer for the data image analysis task; the computer delivers the answer to a user interface.

Artificial intelligence generated synthetic image data for use with machine language models

Method, apparatus, and computer program product are provided for retrieving analogues using topological knowledge representation (TKR). In some embodiments, a TKR input query is built and/or validated using a domain-specific knowledge base (KB). A search database containing candidate analogues and corresponding pre-built TKRs is then searched to retrieve at least one analogue of the TKR input query using statistical analysis. In some embodiments, a system may build the TKR input query based on a seismic dataset. For example, the system may receive a seismic dataset, segment the seismic dataset and classify each region using a computer vision (CV) database and the KB, and build the TKR input query based on the segmented and classified seismic dataset. In some embodiments, the TKR input query may be input and/or edited by a user. For example, the TKR input query may be input and/or edited by the user and validated using the KB.

Searching for analogue subsurface structures based on topological knowledge representation (TKR)

Data associated with a region, acquired by a robot may be passed to a previously trained classifier. The classifier outputs a classification label L, and a confidence score C. Responsive to determining that the confidence score C is below a threshold T, the acquired data can be added to a training data set associated with the classifier, and the classifier retrained using the training data set which include at least information from the acquired data. Responsive to determining that the confidence score C is below the threshold T, at least one candidate region having characteristic similarity to the region can be identified. Responsive to determining that the confidence score C is not below the threshold T, at least one candidate region having a different characteristic from the region can be identified. The robot may be caused to acquire data associated with the candidate region.

Online utility-driven spatially-referenced data collector for classification

A real-time route determination system includes one or more communication devices in signal communication with a route server system. Each communication device is configured to receive one or both of vehicle data and user data to determine a stress-level based on one or both of the vehicle data and the user data. The route server system is configured to determine at least one navigation route in real-time based in part on the stress-level, and to output a route signal indicative of the at least one navigation route. The communication device displays a graphical map including a graphical route displaying the at least one navigation route.

Real-time route determination based on localized information

Techniques relate to adapting communications. A computer system receives initial content and event constraints related to a to-be-delivered communication and extracts information for recipients designated to receive the to-be-delivered communication. The computer system determines content utility values for topics of the initial content for each of the recipients, the content utility values for each of the topics being based on the information for each of the recipients. The computer system determines total content utility values for each of the topics in the initial content and selects elements of the to-be-delivered communication from a database based at least in part on the total content utility values for the topics and the event constraints.

Adapting communications according to audience profile from social media

The present disclosure describes systems and methods for identifying products that are implicitly published in an image, e.g., where there is no identifying text or comments that identify the brand of the product. A product entity may be identified based on comments posted in response to the posting of the image. An analysis of the image may be performed based on the identified product entity to find items or products of a type of the identified product entity in the image. A product detected in the image may be compared to a database of products of the type of product entity to determine which product was posted in the image.

Processing image using narrowed search space based on textual context to detect items in the image

A technique relates to tracking a foodstuff. A device images human consumable code formed on the foodstuff, the human consumable code being part of the foodstuff, the foodstuff being unpackaged. A coding associated with the human consumable code is determined. Product information of the foodstuff is retrieved from a computer system by using the coding. The product information of the foodstuff is provided on the device.

Image-based encoding

A method, computer system, and a computer program product for access control is provided. The present invention may include requesting a random gesture challenge, wherein the requested random gesture challenge includes an expected response associated with an authorized user. The present invention may include, in response to receiving a video data, determining whether the received video data includes a user response matching the expected response. The present invention may include determining whether a first heartbeat signal of a user matches a second heartbeat signal measured based on the received video data. The present invention may include, in response to determining a first match between the user response included in the received video data and the expected response and a second match between the first heartbeat signal and the second heartbeat signal, authenticating the user as the authorized user of the user device.

Access control using multi-authentication factors

A method for improving the performance of a computer vision system includes obtaining input specifying a task to be performed by the computer vision system; obtaining a first digital image; and comparing the first digital image to at least one training image used to train the computer vision system to solve the task. Further steps include, based on the comparing indicating that the first digital image is insufficiently similar to the at least one training image, recommending at least one adjustment to the digital image; obtaining a second digital image in accordance with the adjustment; and performing the task with the computer vision system based on the second digital image obtained in accordance with the adjustment. Adjustments can be based, for example, on image composition and/or weather conditions.

Advising image acquisition based on existing training sets

An online learning system selects content for a learning session and opens a user interface to start the learning session on a plurality of devices. A mode of instruction is selected for the learning session. An activity to perform associated with the content is presented. Performance of the activity is monitored and a performance metric and/or a heterogeneity metric associated with a key performance indicator for the activity performed is generated. Responsive to determining that the performance metric and/or a heterogeneity metric is outside of the target range, the mode of instruction may be switched automatically.

Learning systems and automatic transitioning between learning systems

Techniques for image analysis and configuration modification are provided. A first context of a camera device is determined, where the first context includes a current location of the camera device. A plurality of prior images is identified based on the first context, where each of the plurality of prior images was captured within a predefined distance from the current location of the camera device. Further, a respective popularity score is generated for each of the plurality of prior images, based on one or more social media networks. Finally, a first set of configuration parameters is generated for the camera device, based at least in part on (i) a degree of difference between the first context and a second context associated with a first prior image of the plurality of prior images, and (ii) a first popularity score of the first prior image.

Generating image capture configurations and compositions

An image of a region captured by an unmanned aerial vehicle flying at an altitude may be received. A computer vision algorithm may be executed with the image as an input to compute an overall confidence score associated with detecting one or more candidate objects in the image. Responsive to determining that the confidence score is below a predefined minimum threshold or above a predefined maximum threshold, the unmanned aerial vehicle may be controlled to change its altitude and recapture the image of the region at a new position. Responsive to determining that the overall confidence score is not below the predefined minimum threshold, information associated with the image may be stored on a storage device.

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Sao Paulo, Brazil

Andrea Britto Mattos Lima