FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3197363678> ?p ?o ?g. }

• W3197363678 abstract "Cervical cancer is a very common and fatal type of cancer in women. Cytopathology images are often used to screen for this cancer. Given that there is a possibility that many errors can occur during manual screening, a computer-aided diagnosis system based on deep learning has been developed. Deep learning methods require a fixed dimension of input images, but the dimensions of clinical medical images are inconsistent. The aspect ratios of the images suffer while resizing them directly. Clinically, the aspect ratios of cells inside cytopathological images provide important information for doctors to diagnose cancer. Therefore, it is difficult to resize directly. However, many existing studies have resized the images directly and have obtained highly robust classification results. To determine a reasonable interpretation, we have conducted a series of comparative experiments. First, the raw data of the SIPaKMeD dataset are pre-processed to obtain standard and scaled datasets. Then, the datasets are resized to 224 x 224 pixels. Finally, 22 deep learning models are used to classify the standard and scaled datasets. The results of the study indicate that deep learning models are robust to changes in the aspect ratio of cells in cervical cytopathological images. This conclusion is also validated via the Herlev dataset." @default.
• W3197363678 created "2021-09-13" @default.
• W3197363678 creator A5007442731 @default.
• W3197363678 creator A5010560844 @default.
• W3197363678 creator A5021104232 @default.
• W3197363678 creator A5021827481 @default.
• W3197363678 creator A5024292688 @default.
• W3197363678 creator A5032447166 @default.
• W3197363678 creator A5037990310 @default.
• W3197363678 creator A5047332568 @default.
• W3197363678 creator A5056661303 @default.
• W3197363678 date "2021-05-16" @default.
• W3197363678 modified "2023-10-16" @default.
• W3197363678 title "Is the aspect ratio of cells important in deep learning? A robust comparison of deep learning methods for multi-scale cytopathology cell image classification: from convolutional neural networks to visual transformers" @default.
• W3197363678 cites W2010241060 @default.
• W3197363678 cites W2015861736 @default.
• W3197363678 cites W2097117768 @default.
• W3197363678 cites W2098360374 @default.
• W3197363678 cites W2183341477 @default.
• W3197363678 cites W2194775991 @default.
• W3197363678 cites W2320641533 @default.
• W3197363678 cites W2344654247 @default.
• W3197363678 cites W2398921440 @default.
• W3197363678 cites W2531409750 @default.
• W3197363678 cites W2557283755 @default.
• W3197363678 cites W2594262533 @default.
• W3197363678 cites W2725194261 @default.
• W3197363678 cites W2726146029 @default.
• W3197363678 cites W2883780447 @default.
• W3197363678 cites W2889242407 @default.
• W3197363678 cites W2892046320 @default.
• W3197363678 cites W2907329590 @default.
• W3197363678 cites W2919115771 @default.
• W3197363678 cites W2924609556 @default.
• W3197363678 cites W2938286185 @default.
• W3197363678 cites W2972574169 @default.
• W3197363678 cites W2990162747 @default.
• W3197363678 cites W3009901339 @default.
• W3197363678 cites W3014001067 @default.
• W3197363678 cites W3024740627 @default.
• W3197363678 cites W3034124771 @default.
• W3197363678 cites W3093496925 @default.
• W3197363678 cites W3102737931 @default.
• W3197363678 cites W3130039502 @default.
• W3197363678 cites W3133063036 @default.
• W3197363678 cites W3170874841 @default.
• W3197363678 cites W3172509117 @default.
• W3197363678 cites W3181029726 @default.
• W3197363678 cites W2985532529 @default.
• W3197363678 doi "https://doi.org/10.48550/arxiv.2105.07402" @default.
• W3197363678 hasPublicationYear "2021" @default.
• W3197363678 type Work @default.
• W3197363678 sameAs 3197363678 @default.
• W3197363678 citedByCount "0" @default.
• W3197363678 crossrefType "posted-content" @default.
• W3197363678 hasAuthorship W3197363678A5007442731 @default.
• W3197363678 hasAuthorship W3197363678A5010560844 @default.
• W3197363678 hasAuthorship W3197363678A5021104232 @default.
• W3197363678 hasAuthorship W3197363678A5021827481 @default.
• W3197363678 hasAuthorship W3197363678A5024292688 @default.
• W3197363678 hasAuthorship W3197363678A5032447166 @default.
• W3197363678 hasAuthorship W3197363678A5037990310 @default.
• W3197363678 hasAuthorship W3197363678A5047332568 @default.
• W3197363678 hasAuthorship W3197363678A5056661303 @default.
• W3197363678 hasBestOaLocation W31973636781 @default.
• W3197363678 hasConcept C108583219 @default.
• W3197363678 hasConcept C119857082 @default.
• W3197363678 hasConcept C142724271 @default.
• W3197363678 hasConcept C153180895 @default.
• W3197363678 hasConcept C154945302 @default.
• W3197363678 hasConcept C160633673 @default.
• W3197363678 hasConcept C18823058 @default.
• W3197363678 hasConcept C2778654104 @default.
• W3197363678 hasConcept C2984842247 @default.
• W3197363678 hasConcept C41008148 @default.
• W3197363678 hasConcept C71924100 @default.
• W3197363678 hasConcept C81363708 @default.
• W3197363678 hasConceptScore W3197363678C108583219 @default.
• W3197363678 hasConceptScore W3197363678C119857082 @default.
• W3197363678 hasConceptScore W3197363678C142724271 @default.
• W3197363678 hasConceptScore W3197363678C153180895 @default.
• W3197363678 hasConceptScore W3197363678C154945302 @default.
• W3197363678 hasConceptScore W3197363678C160633673 @default.
• W3197363678 hasConceptScore W3197363678C18823058 @default.
• W3197363678 hasConceptScore W3197363678C2778654104 @default.
• W3197363678 hasConceptScore W3197363678C2984842247 @default.
• W3197363678 hasConceptScore W3197363678C41008148 @default.
• W3197363678 hasConceptScore W3197363678C71924100 @default.
• W3197363678 hasConceptScore W3197363678C81363708 @default.
• W3197363678 hasLocation W31973636781 @default.
• W3197363678 hasOpenAccess W3197363678 @default.
• W3197363678 hasPrimaryLocation W31973636781 @default.
• W3197363678 hasRelatedWork W2279398222 @default.
• W3197363678 hasRelatedWork W2726121760 @default.
• W3197363678 hasRelatedWork W2732542196 @default.
• W3197363678 hasRelatedWork W2738221750 @default.
• W3197363678 hasRelatedWork W2915754718 @default.
• W3197363678 hasRelatedWork W3021430260 @default.
• W3197363678 hasRelatedWork W4299822940 @default.
• W3197363678 hasRelatedWork W4311257506 @default.

• next