FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3212643684> ?p ?o ?g. }

• W3212643684 endingPage "1271" @default.
• W3212643684 startingPage "1255" @default.
• W3212643684 abstract "Notwithstanding the discovery of vaccines for Covid-19, the virus's rapid spread continues due to the limited availability of vaccines, especially in poor and emerging countries. Therefore, the key issues in the present COVID-19 pandemic are the early identification of COVID-19, the cautious separation of infected cases at the lowest cost and curing the disease in the early stages. For that reason, the methodology adopted for this study is imaging tools, particularly computed tomography, which have been critical in diagnosing and treating the disease. A new method for detecting Covid-19 in X-rays and CT images has been presented based on the Scatter Wavelet Transform and Dense Deep Neural Network. The Scatter Wavelet Transform has been employed as a feature extractor, while the Dense Deep Neural Network is utilized as a binary classifier. An extensive experiment was carried out to evaluate the accuracy of the proposed method over three datasets: IEEE 80200, Kaggle, and Covid-19 X-ray image data Sets. The dataset used in the experimental part consists of 14142. The numbers of training and testing images are 8290 and 2810, respectively. The analysis of the result refers that the proposed methods achieved high accuracy of 98%. The proposed model results show an excellent outcome compared to other methods in the same domain, such as (DeTraC) CNN, which achieved only 93.1%, CNN, which achieved 94%, and stacked Multi-Resolution CovXNet, which achieved 97.4%. The accuracy of CapsNet reached 97.24%." @default.
• W3212643684 created "2021-11-22" @default.
• W3212643684 creator A5001633064 @default.
• W3212643684 creator A5052553220 @default.
• W3212643684 creator A5085541329 @default.
• W3212643684 date "2022-01-01" @default.
• W3212643684 modified "2023-09-27" @default.
• W3212643684 title "X-Ray Covid-19 Detection Based on Scatter Wavelet Transform and Dense Deep Neural Network" @default.
• W3212643684 cites W1994906459 @default.
• W3212643684 cites W2065630216 @default.
• W3212643684 cites W2093231248 @default.
• W3212643684 cites W2105637133 @default.
• W3212643684 cites W2134061616 @default.
• W3212643684 cites W2792680145 @default.
• W3212643684 cites W2903899730 @default.
• W3212643684 cites W2908201961 @default.
• W3212643684 cites W2938879599 @default.
• W3212643684 cites W2953532875 @default.
• W3212643684 cites W2981092563 @default.
• W3212643684 cites W2989673213 @default.
• W3212643684 cites W3001118548 @default.
• W3212643684 cites W3001456238 @default.
• W3212643684 cites W3001897055 @default.
• W3212643684 cites W3002539152 @default.
• W3212643684 cites W3003217347 @default.
• W3212643684 cites W3003639008 @default.
• W3212643684 cites W3003790823 @default.
• W3212643684 cites W3004280078 @default.
• W3212643684 cites W3005473082 @default.
• W3212643684 cites W3007497549 @default.
• W3212643684 cites W3007580879 @default.
• W3212643684 cites W3008090866 @default.
• W3212643684 cites W3008627212 @default.
• W3212643684 cites W3008985036 @default.
• W3212643684 cites W3009906937 @default.
• W3212643684 cites W3010381061 @default.
• W3212643684 cites W3010699833 @default.
• W3212643684 cites W3011102168 @default.
• W3212643684 cites W3011149445 @default.
• W3212643684 cites W3012102172 @default.
• W3212643684 cites W3013306614 @default.
• W3212643684 cites W3017117984 @default.
• W3212643684 cites W3017855299 @default.
• W3212643684 cites W3019677466 @default.
• W3212643684 cites W3020052412 @default.
• W3212643684 cites W3023349249 @default.
• W3212643684 cites W3036638392 @default.
• W3212643684 cites W3041148517 @default.
• W3212643684 cites W3083753334 @default.
• W3212643684 cites W3092385950 @default.
• W3212643684 cites W3102503485 @default.
• W3212643684 cites W3137180645 @default.
• W3212643684 cites W3162351260 @default.
• W3212643684 cites W4205947740 @default.
• W3212643684 cites W4252949347 @default.
• W3212643684 doi "https://doi.org/10.32604/csse.2022.021980" @default.
• W3212643684 hasPublicationYear "2022" @default.
• W3212643684 type Work @default.
• W3212643684 sameAs 3212643684 @default.
• W3212643684 citedByCount "4" @default.
• W3212643684 countsByYear W32126436842022 @default.
• W3212643684 countsByYear W32126436842023 @default.
• W3212643684 crossrefType "journal-article" @default.
• W3212643684 hasAuthorship W3212643684A5001633064 @default.
• W3212643684 hasAuthorship W3212643684A5052553220 @default.
• W3212643684 hasAuthorship W3212643684A5085541329 @default.
• W3212643684 hasBestOaLocation W32126436841 @default.
• W3212643684 hasConcept C108583219 @default.
• W3212643684 hasConcept C117978034 @default.
• W3212643684 hasConcept C127413603 @default.
• W3212643684 hasConcept C142724271 @default.
• W3212643684 hasConcept C153180895 @default.
• W3212643684 hasConcept C154945302 @default.
• W3212643684 hasConcept C196216189 @default.
• W3212643684 hasConcept C21880701 @default.
• W3212643684 hasConcept C2779134260 @default.
• W3212643684 hasConcept C3008058167 @default.
• W3212643684 hasConcept C41008148 @default.
• W3212643684 hasConcept C47432892 @default.
• W3212643684 hasConcept C50644808 @default.
• W3212643684 hasConcept C524204448 @default.
• W3212643684 hasConcept C71924100 @default.
• W3212643684 hasConcept C81363708 @default.
• W3212643684 hasConcept C95623464 @default.
• W3212643684 hasConceptScore W3212643684C108583219 @default.
• W3212643684 hasConceptScore W3212643684C117978034 @default.
• W3212643684 hasConceptScore W3212643684C127413603 @default.
• W3212643684 hasConceptScore W3212643684C142724271 @default.
• W3212643684 hasConceptScore W3212643684C153180895 @default.
• W3212643684 hasConceptScore W3212643684C154945302 @default.
• W3212643684 hasConceptScore W3212643684C196216189 @default.
• W3212643684 hasConceptScore W3212643684C21880701 @default.
• W3212643684 hasConceptScore W3212643684C2779134260 @default.
• W3212643684 hasConceptScore W3212643684C3008058167 @default.
• W3212643684 hasConceptScore W3212643684C41008148 @default.
• W3212643684 hasConceptScore W3212643684C47432892 @default.
• W3212643684 hasConceptScore W3212643684C50644808 @default.
• W3212643684 hasConceptScore W3212643684C524204448 @default.

• next