Matches in SemOpenAlex for { <https://semopenalex.org/work/W4380882728> ?p ?o ?g. }
Showing items 1 to 74 of
74
with 100 items per page.
- W4380882728 endingPage "100817" @default.
- W4380882728 startingPage "100817" @default.
- W4380882728 abstract "Images using OCT (Optical Coherence Tomography) for producing cross-sections of images of retina light-sensitive tissue linings behind the human eye's black portions. Segmentation provides a better understanding of the retinal anatomy, which is essential in planning and evaluating treatment options. By measuring retinal thickness and analyzing the arrangement of retinal tissue. A semantic segmentation model based on U-Net deep learning model is proposed. It uses ResNet34 architecture as an encoder and decoder for efficient feature extraction from the input images. A complete convolution encoder-decoder network called U-Net has skip links between the blocks that deal with symmetric encoding and decoding. The proposed framework can segment the layers in the OCT scan accurately.As the light returns to the scanner from the retina, it provides fine-grained cross-sectional photographs of the retina.The effectiveness of the suggested strategy was evaluated at two benchmarks: DeepLabV3Plus and UnetP++.Accuracy and mean Intersection over Union (mIoU) were two of the typical pixel-wise measures that were taken into consideration while evaluating the models' effectiveness. The future enhancement of this work (1) Add other performance evaluation metrics like transmission time, precision, and recall, (2) Deep learning approach use optimization algorithms to improve accuracy value." @default.
- W4380882728 created "2023-06-17" @default.
- W4380882728 creator A5020614211 @default.
- W4380882728 creator A5047546629 @default.
- W4380882728 date "2023-10-01" @default.
- W4380882728 modified "2023-10-18" @default.
- W4380882728 title "OCT layer segmentation using U-NET semantic segmentation and RESNET34 encoder-decoder" @default.
- W4380882728 cites W2920304367 @default.
- W4380882728 cites W2936532844 @default.
- W4380882728 cites W2970650116 @default.
- W4380882728 cites W2997639937 @default.
- W4380882728 cites W3021316603 @default.
- W4380882728 cites W3025004856 @default.
- W4380882728 cites W3025858451 @default.
- W4380882728 cites W3108717672 @default.
- W4380882728 cites W3161567445 @default.
- W4380882728 cites W3189659869 @default.
- W4380882728 cites W3195514151 @default.
- W4380882728 cites W4280519468 @default.
- W4380882728 doi "https://doi.org/10.1016/j.measen.2023.100817" @default.
- W4380882728 hasPublicationYear "2023" @default.
- W4380882728 type Work @default.
- W4380882728 citedByCount "0" @default.
- W4380882728 crossrefType "journal-article" @default.
- W4380882728 hasAuthorship W4380882728A5020614211 @default.
- W4380882728 hasAuthorship W4380882728A5047546629 @default.
- W4380882728 hasBestOaLocation W43808827281 @default.
- W4380882728 hasConcept C111919701 @default.
- W4380882728 hasConcept C118505674 @default.
- W4380882728 hasConcept C120665830 @default.
- W4380882728 hasConcept C121332964 @default.
- W4380882728 hasConcept C124504099 @default.
- W4380882728 hasConcept C138885662 @default.
- W4380882728 hasConcept C153180895 @default.
- W4380882728 hasConcept C154945302 @default.
- W4380882728 hasConcept C2776401178 @default.
- W4380882728 hasConcept C2778818243 @default.
- W4380882728 hasConcept C31972630 @default.
- W4380882728 hasConcept C41008148 @default.
- W4380882728 hasConcept C41895202 @default.
- W4380882728 hasConcept C89600930 @default.
- W4380882728 hasConceptScore W4380882728C111919701 @default.
- W4380882728 hasConceptScore W4380882728C118505674 @default.
- W4380882728 hasConceptScore W4380882728C120665830 @default.
- W4380882728 hasConceptScore W4380882728C121332964 @default.
- W4380882728 hasConceptScore W4380882728C124504099 @default.
- W4380882728 hasConceptScore W4380882728C138885662 @default.
- W4380882728 hasConceptScore W4380882728C153180895 @default.
- W4380882728 hasConceptScore W4380882728C154945302 @default.
- W4380882728 hasConceptScore W4380882728C2776401178 @default.
- W4380882728 hasConceptScore W4380882728C2778818243 @default.
- W4380882728 hasConceptScore W4380882728C31972630 @default.
- W4380882728 hasConceptScore W4380882728C41008148 @default.
- W4380882728 hasConceptScore W4380882728C41895202 @default.
- W4380882728 hasConceptScore W4380882728C89600930 @default.
- W4380882728 hasLocation W43808827281 @default.
- W4380882728 hasOpenAccess W4380882728 @default.
- W4380882728 hasPrimaryLocation W43808827281 @default.
- W4380882728 hasRelatedWork W1669643531 @default.
- W4380882728 hasRelatedWork W1982826852 @default.
- W4380882728 hasRelatedWork W2005437358 @default.
- W4380882728 hasRelatedWork W2008656436 @default.
- W4380882728 hasRelatedWork W2023558673 @default.
- W4380882728 hasRelatedWork W2110230079 @default.
- W4380882728 hasRelatedWork W2134924024 @default.
- W4380882728 hasRelatedWork W2517104666 @default.
- W4380882728 hasRelatedWork W2613186388 @default.
- W4380882728 hasRelatedWork W1967061043 @default.
- W4380882728 hasVolume "29" @default.
- W4380882728 isParatext "false" @default.
- W4380882728 isRetracted "false" @default.
- W4380882728 workType "article" @default.