Comparison among common backbone networks on the ImageNet-1k dataset.
<p>Comparison among common backbone networks on the ImageNet-1k dataset.</p>
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , , |
| منشور في: |
2024
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| الموضوعات: | |
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| _version_ | 1852024242856525824 |
|---|---|
| author | Zhuolin Yang (14658411) |
| author2 | Zhen Cao (30837) Jianfang Cao (1881379) Zhiqiang Chen (218692) Cunhe Peng (20454990) |
| author2_role | author author author author |
| author_facet | Zhuolin Yang (14658411) Zhen Cao (30837) Jianfang Cao (1881379) Zhiqiang Chen (218692) Cunhe Peng (20454990) |
| author_role | author |
| dc.creator.none.fl_str_mv | Zhuolin Yang (14658411) Zhen Cao (30837) Jianfang Cao (1881379) Zhiqiang Chen (218692) Cunhe Peng (20454990) |
| dc.date.none.fl_str_mv | 2024-12-19T18:44:06Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0315621.t007 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/Comparison_among_common_backbone_networks_on_the_ImageNet-1k_dataset_/28065573 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Medicine Science Policy Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified segmentation effect achieved resulting segmentation accuracy pixel classification process experimental results show deep supervision layers convolutional layer deepens edge segmentation effect spatial detail information edge optimization module category perception module express edge features edge optimization edge features redundant information effective information connect features xlink "> significantly lower proposed method methods fail may cause fully use ecmnet ). different scales different resolutions cityspaces dataset camvid dataset adaptive algorithm |
| dc.title.none.fl_str_mv | Comparison among common backbone networks on the ImageNet-1k dataset. |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <p>Comparison among common backbone networks on the ImageNet-1k dataset.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_a074f648775a549fbae5bd251ea401b8 |
| identifier_str_mv | 10.1371/journal.pone.0315621.t007 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/28065573 |
| publishDate | 2024 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Comparison among common backbone networks on the ImageNet-1k dataset.Zhuolin Yang (14658411)Zhen Cao (30837)Jianfang Cao (1881379)Zhiqiang Chen (218692)Cunhe Peng (20454990)MedicineScience PolicySpace ScienceBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedsegmentation effect achievedresulting segmentation accuracypixel classification processexperimental results showdeep supervision layersconvolutional layer deepensedge segmentation effectspatial detail informationedge optimization modulecategory perception moduleexpress edge featuresedge optimizationedge featuresredundant informationeffective informationconnect featuresxlink ">significantly lowerproposed methodmethods failmay causefully useecmnet ).different scalesdifferent resolutionscityspaces datasetcamvid datasetadaptive algorithm<p>Comparison among common backbone networks on the ImageNet-1k dataset.</p>2024-12-19T18:44:06ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0315621.t007https://figshare.com/articles/dataset/Comparison_among_common_backbone_networks_on_the_ImageNet-1k_dataset_/28065573CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/280655732024-12-19T18:44:06Z |
| spellingShingle | Comparison among common backbone networks on the ImageNet-1k dataset. Zhuolin Yang (14658411) Medicine Science Policy Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified segmentation effect achieved resulting segmentation accuracy pixel classification process experimental results show deep supervision layers convolutional layer deepens edge segmentation effect spatial detail information edge optimization module category perception module express edge features edge optimization edge features redundant information effective information connect features xlink "> significantly lower proposed method methods fail may cause fully use ecmnet ). different scales different resolutions cityspaces dataset camvid dataset adaptive algorithm |
| status_str | publishedVersion |
| title | Comparison among common backbone networks on the ImageNet-1k dataset. |
| title_full | Comparison among common backbone networks on the ImageNet-1k dataset. |
| title_fullStr | Comparison among common backbone networks on the ImageNet-1k dataset. |
| title_full_unstemmed | Comparison among common backbone networks on the ImageNet-1k dataset. |
| title_short | Comparison among common backbone networks on the ImageNet-1k dataset. |
| title_sort | Comparison among common backbone networks on the ImageNet-1k dataset. |
| topic | Medicine Science Policy Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified segmentation effect achieved resulting segmentation accuracy pixel classification process experimental results show deep supervision layers convolutional layer deepens edge segmentation effect spatial detail information edge optimization module category perception module express edge features edge optimization edge features redundant information effective information connect features xlink "> significantly lower proposed method methods fail may cause fully use ecmnet ). different scales different resolutions cityspaces dataset camvid dataset adaptive algorithm |