Multi-level feature aggregation and context enhancement network.
<p>Multi-level feature aggregation and context enhancement network.</p>
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2025
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| _version_ | 1852017818618298368 |
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| author | Xichun Chen (22001791) |
| author2 | Yu Tian (367745) Ming Li (91180) Bin Lv (551701) Shuo Zhang (30844) Zixian Qu (21568078) Jianqing Wu (163999) Shiya Cheng (6593378) |
| author2_role | author author author author author author author |
| author_facet | Xichun Chen (22001791) Yu Tian (367745) Ming Li (91180) Bin Lv (551701) Shuo Zhang (30844) Zixian Qu (21568078) Jianqing Wu (163999) Shiya Cheng (6593378) |
| author_role | author |
| dc.creator.none.fl_str_mv | Xichun Chen (22001791) Yu Tian (367745) Ming Li (91180) Bin Lv (551701) Shuo Zhang (30844) Zixian Qu (21568078) Jianqing Wu (163999) Shiya Cheng (6593378) |
| dc.date.none.fl_str_mv | 2025-08-06T17:39:08Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0329303.g001 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Multi-level_feature_aggregation_and_context_enhancement_network_/29846596 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biotechnology Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified wise feature representation varying environmental conditions score also rises sampling positions according network architecture integrates limited resource conditions level feature aggregation irregularly shaped intrusions improve localization robustness experimental results demonstrate context enhancement network 8 %&# 8212 macenet </ p actual object shapes yolo module study proposes specific datasets refine spatial notable increase net ). loss function improving map generalized intersection dynamically adapt dcnv3 allows dcnv3 ). constrained energy automatic detection 200 images 2 %. |
| dc.title.none.fl_str_mv | Multi-level feature aggregation and context enhancement network. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>Multi-level feature aggregation and context enhancement network.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_cc710ee917cefa813bc267bacb24b68c |
| identifier_str_mv | 10.1371/journal.pone.0329303.g001 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/29846596 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Multi-level feature aggregation and context enhancement network.Xichun Chen (22001791)Yu Tian (367745)Ming Li (91180)Bin Lv (551701)Shuo Zhang (30844)Zixian Qu (21568078)Jianqing Wu (163999)Shiya Cheng (6593378)BiotechnologySpace ScienceBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedwise feature representationvarying environmental conditionsscore also risessampling positions accordingnetwork architecture integrateslimited resource conditionslevel feature aggregationirregularly shaped intrusionsimprove localization robustnessexperimental results demonstratecontext enhancement network8 %&# 8212macenet </ pactual object shapesyolo modulestudy proposesspecific datasetsrefine spatialnotable increasenet ).loss functionimproving mapgeneralized intersectiondynamically adaptdcnv3 allowsdcnv3 ).constrained energyautomatic detection200 images2 %.<p>Multi-level feature aggregation and context enhancement network.</p>2025-08-06T17:39:08ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0329303.g001https://figshare.com/articles/figure/Multi-level_feature_aggregation_and_context_enhancement_network_/29846596CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/298465962025-08-06T17:39:08Z |
| spellingShingle | Multi-level feature aggregation and context enhancement network. Xichun Chen (22001791) Biotechnology Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified wise feature representation varying environmental conditions score also rises sampling positions according network architecture integrates limited resource conditions level feature aggregation irregularly shaped intrusions improve localization robustness experimental results demonstrate context enhancement network 8 %&# 8212 macenet </ p actual object shapes yolo module study proposes specific datasets refine spatial notable increase net ). loss function improving map generalized intersection dynamically adapt dcnv3 allows dcnv3 ). constrained energy automatic detection 200 images 2 %. |
| status_str | publishedVersion |
| title | Multi-level feature aggregation and context enhancement network. |
| title_full | Multi-level feature aggregation and context enhancement network. |
| title_fullStr | Multi-level feature aggregation and context enhancement network. |
| title_full_unstemmed | Multi-level feature aggregation and context enhancement network. |
| title_short | Multi-level feature aggregation and context enhancement network. |
| title_sort | Multi-level feature aggregation and context enhancement network. |
| topic | Biotechnology Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified wise feature representation varying environmental conditions score also rises sampling positions according network architecture integrates limited resource conditions level feature aggregation irregularly shaped intrusions improve localization robustness experimental results demonstrate context enhancement network 8 %&# 8212 macenet </ p actual object shapes yolo module study proposes specific datasets refine spatial notable increase net ). loss function improving map generalized intersection dynamically adapt dcnv3 allows dcnv3 ). constrained energy automatic detection 200 images 2 %. |