_version_ 1852017818618298368
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 %.