The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
May. 21, 2024
Filed:
Mar. 05, 2021
International Business Machines Corporation, Armonk, NY (US);
Petrogal Brasil S.a., Rio de Janeiro, BR;
Emilio Ashton Vital Brazil, Rio de Janeiro, BR;
Rodrigo da Silva Ferreira, Rio de Janeiro, BR;
Viviane Torres da Silva, Laranjeiras, BR;
Renato Fontoura de Gusmao Cerqueira, Rio de Janeiro, BR;
Raphael Melo Thiago, Rio de Janeiro, BR;
Elton Figueiredo de Souza Soares, Rio de Janeiro, BR;
Leonardo Guerreiro Azevedo, Rio de Janeiro, BR;
Vinicius Costa Villas Boas Segura, Rio de Janeiro, BR;
Ana Fucs, Rio de Janeiro, BR;
Juliana Jansen Ferreira, Rio de Janeiro, BR;
Joana de Noronha Ribeiro de Almeida, Lisbon, PT;
Bruno Felix Carvalho, Lisbon, PT;
Dario Sergio Cersosimo, Lisbon, PT;
Marco Daniel Melo Ferraz, Oeiras, PT;
International Business Machines Corporation, Armonk, NY (US);
Abstract
Machine teaching in an embodiment can include receiving a user annotated concept for a given image in given context. The given image can be broken into parts and classified. Relationships can be determined associated with the parts. The created relationships can be stored along with the user annotated concept in a knowledge base. One or more similar images can be annotated using the parts and relationships. A second image associated the given context can be retrieved, decomposed into parts. The parts can be classified. Relationships can be determined associated with the second image's parts. Classifications and relationships associated with the second image's parts can be compared with classifications and relationships associated with the given image's parts. Based on comparing, the second image can be annotated with the user annotated concept for the given image.