Matches in SemOpenAlex for { <https://semopenalex.org/work/W4380147950> ?p ?o ?g. }
Showing items 1 to 76 of
76
with 100 items per page.
- W4380147950 endingPage "105" @default.
- W4380147950 startingPage "91" @default.
- W4380147950 abstract "Predicting a class or label of text-aided image has practical application in a range of domains including social media, machine learning and medical domain. Usually, supervised learning model is used to make such predictions where labeled data is mandatory, which is time consuming and required manual help. Classification of images are accomplished on visual features only by utilizing deep learning. Employing semi-supervised learning is a viable answer to these issues that needs a few label sample to classify huge unlabeled samples. The paper suggests a novel semi-supervised deep learning method based on fuzziness, called (FSSDL-MIC) for multimodal image classification to tackle the challenge of web image classification. For the first time in this scenario, we integrate Multilayer perceptron for textual features and MobileNetV2 for visual features to create a multimodal paradigm. Using data from PASCAL VOC’07, experiments have revealed that the proposed framework achieves significant improvement and outperforms modern techniques for multimodal image categorization. We also see a positive impact of low fuzzy sample when final model trained with visual features only." @default.
- W4380147950 created "2023-06-11" @default.
- W4380147950 creator A5027525633 @default.
- W4380147950 creator A5027540543 @default.
- W4380147950 creator A5092131634 @default.
- W4380147950 creator A5092131635 @default.
- W4380147950 creator A5092131636 @default.
- W4380147950 date "2023-01-01" @default.
- W4380147950 modified "2023-09-25" @default.
- W4380147950 title "Fuzziness Based Semi-supervised Deep Learning for Multimodal Image Classification" @default.
- W4380147950 cites W1981613567 @default.
- W4380147950 cites W1983993164 @default.
- W4380147950 cites W1985583020 @default.
- W4380147950 cites W2006694196 @default.
- W4380147950 cites W2031489346 @default.
- W4380147950 cites W2085348055 @default.
- W4380147950 cites W2345837149 @default.
- W4380147950 cites W2606007357 @default.
- W4380147950 cites W2928823069 @default.
- W4380147950 cites W2950672152 @default.
- W4380147950 cites W3012308819 @default.
- W4380147950 cites W3086383900 @default.
- W4380147950 cites W3162533277 @default.
- W4380147950 cites W4214597395 @default.
- W4380147950 cites W4226041160 @default.
- W4380147950 cites W4281387732 @default.
- W4380147950 doi "https://doi.org/10.1007/978-3-031-34622-4_8" @default.
- W4380147950 hasPublicationYear "2023" @default.
- W4380147950 type Work @default.
- W4380147950 citedByCount "0" @default.
- W4380147950 crossrefType "book-chapter" @default.
- W4380147950 hasAuthorship W4380147950A5027525633 @default.
- W4380147950 hasAuthorship W4380147950A5027540543 @default.
- W4380147950 hasAuthorship W4380147950A5092131634 @default.
- W4380147950 hasAuthorship W4380147950A5092131635 @default.
- W4380147950 hasAuthorship W4380147950A5092131636 @default.
- W4380147950 hasConcept C108583219 @default.
- W4380147950 hasConcept C115961682 @default.
- W4380147950 hasConcept C119857082 @default.
- W4380147950 hasConcept C136389625 @default.
- W4380147950 hasConcept C153180895 @default.
- W4380147950 hasConcept C154945302 @default.
- W4380147950 hasConcept C41008148 @default.
- W4380147950 hasConcept C50644808 @default.
- W4380147950 hasConcept C75294576 @default.
- W4380147950 hasConcept C94124525 @default.
- W4380147950 hasConcept C95623464 @default.
- W4380147950 hasConceptScore W4380147950C108583219 @default.
- W4380147950 hasConceptScore W4380147950C115961682 @default.
- W4380147950 hasConceptScore W4380147950C119857082 @default.
- W4380147950 hasConceptScore W4380147950C136389625 @default.
- W4380147950 hasConceptScore W4380147950C153180895 @default.
- W4380147950 hasConceptScore W4380147950C154945302 @default.
- W4380147950 hasConceptScore W4380147950C41008148 @default.
- W4380147950 hasConceptScore W4380147950C50644808 @default.
- W4380147950 hasConceptScore W4380147950C75294576 @default.
- W4380147950 hasConceptScore W4380147950C94124525 @default.
- W4380147950 hasConceptScore W4380147950C95623464 @default.
- W4380147950 hasLocation W43801479501 @default.
- W4380147950 hasOpenAccess W4380147950 @default.
- W4380147950 hasPrimaryLocation W43801479501 @default.
- W4380147950 hasRelatedWork W2986507176 @default.
- W4380147950 hasRelatedWork W2997541400 @default.
- W4380147950 hasRelatedWork W3208028783 @default.
- W4380147950 hasRelatedWork W4214932115 @default.
- W4380147950 hasRelatedWork W4221136938 @default.
- W4380147950 hasRelatedWork W4225852842 @default.
- W4380147950 hasRelatedWork W4310989423 @default.
- W4380147950 hasRelatedWork W4312192474 @default.
- W4380147950 hasRelatedWork W4380086463 @default.
- W4380147950 hasRelatedWork W564581980 @default.
- W4380147950 isParatext "false" @default.
- W4380147950 isRetracted "false" @default.
- W4380147950 workType "book-chapter" @default.