Matches in SemOpenAlex for { <https://semopenalex.org/work/W2897933510> ?p ?o ?g. }
Showing items 1 to 91 of
91
with 100 items per page.
- W2897933510 abstract "In recent years, approximate nearest neighbor search methods based on hashing have received considerable attention in large-scale data. There are plenty of new algorithms have been created and applied to different applications successfully. However, Due to the coming of big-data era, the data increasing rapidly and constantly. The batch-mode methods cannot process data efficiently. To solve the problem, online hashing has attracted more attention. Online methods can reduce storage and increase speed of computing. But existing online hashing algorithms also have some problems. The first one is the label information often cannot be got. Because of that, supervised approaches are not practicable. Another problem is online hashing methods process data as a stream, so the relations between old data and new arriving data is taken into account. It is the reason why a novel approach is proposed in this paper which combines matrix factorization with the idea of online hashing. This method considers the relationship between the previous data and newly arriving data. In addition, it updates the hashing learning model by the matrix factorization when the new data is arrived. The experimental results demonstrate superiority of the proposed approach. It outperforms most state-of-the-art online hashing methods and batch-mode methods." @default.
- W2897933510 created "2018-10-26" @default.
- W2897933510 creator A5050881992 @default.
- W2897933510 creator A5052304130 @default.
- W2897933510 creator A5063131315 @default.
- W2897933510 creator A5073583719 @default.
- W2897933510 creator A5083468959 @default.
- W2897933510 date "2018-01-01" @default.
- W2897933510 modified "2023-09-28" @default.
- W2897933510 title "Online Matrix Factorization Hashing for Large-Scale Image Retrieval" @default.
- W2897933510 cites W1893754589 @default.
- W2897933510 cites W1974647172 @default.
- W2897933510 cites W2147717514 @default.
- W2897933510 cites W2204148968 @default.
- W2897933510 cites W2293451293 @default.
- W2897933510 cites W2512032049 @default.
- W2897933510 cites W2554234430 @default.
- W2897933510 doi "https://doi.org/10.1007/978-981-13-2922-7_8" @default.
- W2897933510 hasPublicationYear "2018" @default.
- W2897933510 type Work @default.
- W2897933510 sameAs 2897933510 @default.
- W2897933510 citedByCount "0" @default.
- W2897933510 crossrefType "book-chapter" @default.
- W2897933510 hasAuthorship W2897933510A5050881992 @default.
- W2897933510 hasAuthorship W2897933510A5052304130 @default.
- W2897933510 hasAuthorship W2897933510A5063131315 @default.
- W2897933510 hasAuthorship W2897933510A5073583719 @default.
- W2897933510 hasAuthorship W2897933510A5083468959 @default.
- W2897933510 hasConcept C11413529 @default.
- W2897933510 hasConcept C116058348 @default.
- W2897933510 hasConcept C121332964 @default.
- W2897933510 hasConcept C122907437 @default.
- W2897933510 hasConcept C124101348 @default.
- W2897933510 hasConcept C133667856 @default.
- W2897933510 hasConcept C138111711 @default.
- W2897933510 hasConcept C152671427 @default.
- W2897933510 hasConcept C158693339 @default.
- W2897933510 hasConcept C38652104 @default.
- W2897933510 hasConcept C41008148 @default.
- W2897933510 hasConcept C42355184 @default.
- W2897933510 hasConcept C62520636 @default.
- W2897933510 hasConcept C67388219 @default.
- W2897933510 hasConcept C74270461 @default.
- W2897933510 hasConcept C75684735 @default.
- W2897933510 hasConcept C80444323 @default.
- W2897933510 hasConcept C99138194 @default.
- W2897933510 hasConceptScore W2897933510C11413529 @default.
- W2897933510 hasConceptScore W2897933510C116058348 @default.
- W2897933510 hasConceptScore W2897933510C121332964 @default.
- W2897933510 hasConceptScore W2897933510C122907437 @default.
- W2897933510 hasConceptScore W2897933510C124101348 @default.
- W2897933510 hasConceptScore W2897933510C133667856 @default.
- W2897933510 hasConceptScore W2897933510C138111711 @default.
- W2897933510 hasConceptScore W2897933510C152671427 @default.
- W2897933510 hasConceptScore W2897933510C158693339 @default.
- W2897933510 hasConceptScore W2897933510C38652104 @default.
- W2897933510 hasConceptScore W2897933510C41008148 @default.
- W2897933510 hasConceptScore W2897933510C42355184 @default.
- W2897933510 hasConceptScore W2897933510C62520636 @default.
- W2897933510 hasConceptScore W2897933510C67388219 @default.
- W2897933510 hasConceptScore W2897933510C74270461 @default.
- W2897933510 hasConceptScore W2897933510C75684735 @default.
- W2897933510 hasConceptScore W2897933510C80444323 @default.
- W2897933510 hasConceptScore W2897933510C99138194 @default.
- W2897933510 hasLocation W28979335101 @default.
- W2897933510 hasOpenAccess W2897933510 @default.
- W2897933510 hasPrimaryLocation W28979335101 @default.
- W2897933510 hasRelatedWork W2139202902 @default.
- W2897933510 hasRelatedWork W2142881874 @default.
- W2897933510 hasRelatedWork W2162670057 @default.
- W2897933510 hasRelatedWork W2402125293 @default.
- W2897933510 hasRelatedWork W2535352129 @default.
- W2897933510 hasRelatedWork W2593523465 @default.
- W2897933510 hasRelatedWork W2755098865 @default.
- W2897933510 hasRelatedWork W2792102492 @default.
- W2897933510 hasRelatedWork W2897391546 @default.
- W2897933510 hasRelatedWork W2905097026 @default.
- W2897933510 hasRelatedWork W2944642470 @default.
- W2897933510 hasRelatedWork W2955686881 @default.
- W2897933510 hasRelatedWork W2963276379 @default.
- W2897933510 hasRelatedWork W2991342176 @default.
- W2897933510 hasRelatedWork W3006955796 @default.
- W2897933510 hasRelatedWork W3030106177 @default.
- W2897933510 hasRelatedWork W3034876737 @default.
- W2897933510 hasRelatedWork W3035166804 @default.
- W2897933510 hasRelatedWork W3092760908 @default.
- W2897933510 hasRelatedWork W840129875 @default.
- W2897933510 isParatext "false" @default.
- W2897933510 isRetracted "false" @default.
- W2897933510 magId "2897933510" @default.
- W2897933510 workType "book-chapter" @default.