MACHINE TEACHING COMPLEX CONCEPTS ASSISTED BY COMPUTER VISION AND KNOWLEDGE REASONING
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 annotat...
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| creator | VITAL, Emilio SOARES, Elton ALMEIDA, Joana SEGURA, Vinicius FELIX, Bruno CERQUEIRA, Renato FUCS, Ana SILVA, Viviane CERQUEIRA, Raphael FERREIRA, Juliana FERREIRA, Rodrigo AZEVEDO, Leonardo CERSOSIMO, Dário DANIEL, Marco |
| description | 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. |
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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. 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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.</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZAj1dXT28PRzVQhxBTPcFZz9fQN8XCOAtJ-za0BIsIJjcLBncIiri4JTJFgyNMQ1SCHMM9jT30_B0c9FwdvPP9zH1cXdVSHI1THY3w9oCA8Da1piTnEqL5TmZlBwcw1x9tBNLciPTy0uSExOzUstiXcNMDE2MjIwM3c0NCZCCQAMJzAe</recordid><startdate>20240214</startdate><enddate>20240214</enddate><creator>VITAL, Emilio</creator><creator>SOARES, Elton</creator><creator>ALMEIDA, Joana</creator><creator>SEGURA, Vinicius</creator><creator>FELIX, Bruno</creator><creator>CERQUEIRA, Renato</creator><creator>FUCS, Ana</creator><creator>SILVA, Viviane</creator><creator>CERQUEIRA, Raphael</creator><creator>FERREIRA, Juliana</creator><creator>FERREIRA, Rodrigo</creator><creator>AZEVEDO, Leonardo</creator><creator>CERSOSIMO, Dário</creator><creator>DANIEL, Marco</creator><scope>EVB</scope></search><sort><creationdate>20240214</creationdate><title>MACHINE TEACHING COMPLEX CONCEPTS ASSISTED BY COMPUTER VISION AND KNOWLEDGE REASONING</title><author>VITAL, Emilio ; SOARES, Elton ; ALMEIDA, Joana ; SEGURA, Vinicius ; FELIX, Bruno ; CERQUEIRA, Renato ; FUCS, Ana ; SILVA, Viviane ; CERQUEIRA, Raphael ; FERREIRA, Juliana ; FERREIRA, Rodrigo ; AZEVEDO, Leonardo ; CERSOSIMO, Dário ; DANIEL, Marco</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_EP4322067A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng ; fre ; ger</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>VITAL, Emilio</creatorcontrib><creatorcontrib>SOARES, Elton</creatorcontrib><creatorcontrib>ALMEIDA, Joana</creatorcontrib><creatorcontrib>SEGURA, Vinicius</creatorcontrib><creatorcontrib>FELIX, Bruno</creatorcontrib><creatorcontrib>CERQUEIRA, Renato</creatorcontrib><creatorcontrib>FUCS, Ana</creatorcontrib><creatorcontrib>SILVA, Viviane</creatorcontrib><creatorcontrib>CERQUEIRA, Raphael</creatorcontrib><creatorcontrib>FERREIRA, Juliana</creatorcontrib><creatorcontrib>FERREIRA, Rodrigo</creatorcontrib><creatorcontrib>AZEVEDO, Leonardo</creatorcontrib><creatorcontrib>CERSOSIMO, Dário</creatorcontrib><creatorcontrib>DANIEL, Marco</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>VITAL, Emilio</au><au>SOARES, Elton</au><au>ALMEIDA, Joana</au><au>SEGURA, Vinicius</au><au>FELIX, Bruno</au><au>CERQUEIRA, Renato</au><au>FUCS, Ana</au><au>SILVA, Viviane</au><au>CERQUEIRA, Raphael</au><au>FERREIRA, Juliana</au><au>FERREIRA, Rodrigo</au><au>AZEVEDO, Leonardo</au><au>CERSOSIMO, Dário</au><au>DANIEL, Marco</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>MACHINE TEACHING COMPLEX CONCEPTS ASSISTED BY COMPUTER VISION AND KNOWLEDGE REASONING</title><date>2024-02-14</date><risdate>2024</risdate><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.</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING PHYSICS |
| title | MACHINE TEACHING COMPLEX CONCEPTS ASSISTED BY COMPUTER VISION AND KNOWLEDGE REASONING |
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