Matches in SemOpenAlex for { <https://semopenalex.org/work/W3177677752> ?p ?o ?g. }
Showing items 1 to 84 of
84
with 100 items per page.
- W3177677752 endingPage "737" @default.
- W3177677752 startingPage "726" @default.
- W3177677752 abstract "Image classification is an important task in the field of the intelligent security and deep learning methods represented by convolutional neural networks have achieved many great results in this field. Image classification based on deep learning usually performs well on large-scale datasets, but its performance is often greatly limited by the size of the data. When the dataset is not sufficient, the traditional deep learning method cannot perform well on the small-scale datasets and this situation often occurs in practical applications. To address the drawback, we propose a deep learning framework based on the combination of SoftMax classifier and Bayes learning for small-sample image classification. Within this framework, we utilize transfer learning to solve the problem of too few data, and it can also reduce model training time and space costs. At the same time, we make use of the combination of the above two classifiers to improve the effectiveness and accuracy of the model on different datasets. We empirically find that the model has higher classification accuracy and less training time than the general deep learning model on the datasets. The experiment results demonstrate that the proposed method generally has better classification accuracy on the small-scale datasets, compared with mainstream methods." @default.
- W3177677752 created "2021-07-19" @default.
- W3177677752 creator A5016839838 @default.
- W3177677752 creator A5032181314 @default.
- W3177677752 creator A5054472031 @default.
- W3177677752 creator A5056872865 @default.
- W3177677752 date "2021-01-01" @default.
- W3177677752 modified "2023-09-25" @default.
- W3177677752 title "Intelligent Security Image Classification on Small Sample Learning" @default.
- W3177677752 cites W2137825550 @default.
- W3177677752 cites W2161381512 @default.
- W3177677752 cites W2194321275 @default.
- W3177677752 cites W2519882289 @default.
- W3177677752 cites W2739068048 @default.
- W3177677752 cites W2796346823 @default.
- W3177677752 cites W2796600232 @default.
- W3177677752 cites W2913061354 @default.
- W3177677752 cites W2962799101 @default.
- W3177677752 cites W2965417721 @default.
- W3177677752 cites W3015085081 @default.
- W3177677752 cites W3039198011 @default.
- W3177677752 cites W2964461644 @default.
- W3177677752 doi "https://doi.org/10.1007/978-3-030-78609-0_61" @default.
- W3177677752 hasPublicationYear "2021" @default.
- W3177677752 type Work @default.
- W3177677752 sameAs 3177677752 @default.
- W3177677752 citedByCount "1" @default.
- W3177677752 countsByYear W31776777522023 @default.
- W3177677752 crossrefType "book-chapter" @default.
- W3177677752 hasAuthorship W3177677752A5016839838 @default.
- W3177677752 hasAuthorship W3177677752A5032181314 @default.
- W3177677752 hasAuthorship W3177677752A5054472031 @default.
- W3177677752 hasAuthorship W3177677752A5056872865 @default.
- W3177677752 hasConcept C108583219 @default.
- W3177677752 hasConcept C115961682 @default.
- W3177677752 hasConcept C119857082 @default.
- W3177677752 hasConcept C124101348 @default.
- W3177677752 hasConcept C150899416 @default.
- W3177677752 hasConcept C153180895 @default.
- W3177677752 hasConcept C154945302 @default.
- W3177677752 hasConcept C188441871 @default.
- W3177677752 hasConcept C190502265 @default.
- W3177677752 hasConcept C202444582 @default.
- W3177677752 hasConcept C33923547 @default.
- W3177677752 hasConcept C41008148 @default.
- W3177677752 hasConcept C75294576 @default.
- W3177677752 hasConcept C81363708 @default.
- W3177677752 hasConcept C95623464 @default.
- W3177677752 hasConcept C9652623 @default.
- W3177677752 hasConceptScore W3177677752C108583219 @default.
- W3177677752 hasConceptScore W3177677752C115961682 @default.
- W3177677752 hasConceptScore W3177677752C119857082 @default.
- W3177677752 hasConceptScore W3177677752C124101348 @default.
- W3177677752 hasConceptScore W3177677752C150899416 @default.
- W3177677752 hasConceptScore W3177677752C153180895 @default.
- W3177677752 hasConceptScore W3177677752C154945302 @default.
- W3177677752 hasConceptScore W3177677752C188441871 @default.
- W3177677752 hasConceptScore W3177677752C190502265 @default.
- W3177677752 hasConceptScore W3177677752C202444582 @default.
- W3177677752 hasConceptScore W3177677752C33923547 @default.
- W3177677752 hasConceptScore W3177677752C41008148 @default.
- W3177677752 hasConceptScore W3177677752C75294576 @default.
- W3177677752 hasConceptScore W3177677752C81363708 @default.
- W3177677752 hasConceptScore W3177677752C95623464 @default.
- W3177677752 hasConceptScore W3177677752C9652623 @default.
- W3177677752 hasLocation W31776777521 @default.
- W3177677752 hasOpenAccess W3177677752 @default.
- W3177677752 hasPrimaryLocation W31776777521 @default.
- W3177677752 hasRelatedWork W2883041339 @default.
- W3177677752 hasRelatedWork W2909857627 @default.
- W3177677752 hasRelatedWork W3144565540 @default.
- W3177677752 hasRelatedWork W3177677752 @default.
- W3177677752 hasRelatedWork W3189091156 @default.
- W3177677752 hasRelatedWork W4221015625 @default.
- W3177677752 hasRelatedWork W4281716632 @default.
- W3177677752 hasRelatedWork W4288084884 @default.
- W3177677752 hasRelatedWork W4309224979 @default.
- W3177677752 hasRelatedWork W564581980 @default.
- W3177677752 isParatext "false" @default.
- W3177677752 isRetracted "false" @default.
- W3177677752 magId "3177677752" @default.
- W3177677752 workType "book-chapter" @default.