Accuracy & loss curves of the DenseNet201-Infused Parallel SE-CNN for OpenRecycle Dataset.
<p>Accuracy & loss curves of the DenseNet201-Infused Parallel SE-CNN for OpenRecycle Dataset.</p>
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , , |
| منشور في: |
2025
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| الموضوعات: | |
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| _version_ | 1852019659219402752 |
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| author | Md. Minhazul Islam (20632931) |
| author2 | S. M. Mahedy Hasan (19942286) Md. Rakib Hossain (9612524) Md. Palash Uddin (19139222) Md. Al Mamun (12800084) |
| author2_role | author author author author |
| author_facet | Md. Minhazul Islam (20632931) S. M. Mahedy Hasan (19942286) Md. Rakib Hossain (9612524) Md. Palash Uddin (19139222) Md. Al Mamun (12800084) |
| author_role | author |
| dc.creator.none.fl_str_mv | Md. Minhazul Islam (20632931) S. M. Mahedy Hasan (19942286) Md. Rakib Hossain (9612524) Md. Palash Uddin (19139222) Md. Al Mamun (12800084) |
| dc.date.none.fl_str_mv | 2025-06-04T17:48:05Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0324294.g012 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Accuracy_loss_curves_of_the_DenseNet201-Infused_Parallel_SE-CNN_for_OpenRecycle_Dataset_/29239339 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Ecology Science Policy Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified translating theoretical advancements towards sustainable solutions three additional datasets smart cities progress recycling processes depend promoting environmental sustainability promising heightened efficiency model &# 8217 become increasingly vital restoring waste materials enhance waste diversity effective waste collection waste management practices adaptable waste classification waste data xlink "> work presents transparent decision tangible stride successful deployment study presents reducing pollution recent years precise solution paradigm shift original states irrelevant features integrated squeeze including capturing important ones ground implementation focus areas distinguishable features deep learning current context attention mechanism applied strategically accurately identifying |
| dc.title.none.fl_str_mv | Accuracy & loss curves of the DenseNet201-Infused Parallel SE-CNN for OpenRecycle Dataset. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>Accuracy & loss curves of the DenseNet201-Infused Parallel SE-CNN for OpenRecycle Dataset.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_366a3cfcbc17274a0c57947c486c29aa |
| identifier_str_mv | 10.1371/journal.pone.0324294.g012 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/29239339 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Accuracy & loss curves of the DenseNet201-Infused Parallel SE-CNN for OpenRecycle Dataset.Md. Minhazul Islam (20632931)S. M. Mahedy Hasan (19942286)Md. Rakib Hossain (9612524)Md. Palash Uddin (19139222)Md. Al Mamun (12800084)EcologyScience PolicySpace ScienceEnvironmental Sciences not elsewhere classifiedBiological Sciences not elsewhere classifiedtranslating theoretical advancementstowards sustainable solutionsthree additional datasetssmart cities progressrecycling processes dependpromoting environmental sustainabilitypromising heightened efficiencymodel &# 8217become increasingly vitalrestoring waste materialsenhance waste diversityeffective waste collectionwaste management practicesadaptable waste classificationwaste dataxlink ">work presentstransparent decisiontangible stridesuccessful deploymentstudy presentsreducing pollutionrecent yearsprecise solutionparadigm shiftoriginal statesirrelevant featuresintegrated squeezeincluding capturingimportant onesground implementationfocus areasdistinguishable featuresdeep learningcurrent contextattention mechanismapplied strategicallyaccurately identifying<p>Accuracy & loss curves of the DenseNet201-Infused Parallel SE-CNN for OpenRecycle Dataset.</p>2025-06-04T17:48:05ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0324294.g012https://figshare.com/articles/figure/Accuracy_loss_curves_of_the_DenseNet201-Infused_Parallel_SE-CNN_for_OpenRecycle_Dataset_/29239339CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/292393392025-06-04T17:48:05Z |
| spellingShingle | Accuracy & loss curves of the DenseNet201-Infused Parallel SE-CNN for OpenRecycle Dataset. Md. Minhazul Islam (20632931) Ecology Science Policy Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified translating theoretical advancements towards sustainable solutions three additional datasets smart cities progress recycling processes depend promoting environmental sustainability promising heightened efficiency model &# 8217 become increasingly vital restoring waste materials enhance waste diversity effective waste collection waste management practices adaptable waste classification waste data xlink "> work presents transparent decision tangible stride successful deployment study presents reducing pollution recent years precise solution paradigm shift original states irrelevant features integrated squeeze including capturing important ones ground implementation focus areas distinguishable features deep learning current context attention mechanism applied strategically accurately identifying |
| status_str | publishedVersion |
| title | Accuracy & loss curves of the DenseNet201-Infused Parallel SE-CNN for OpenRecycle Dataset. |
| title_full | Accuracy & loss curves of the DenseNet201-Infused Parallel SE-CNN for OpenRecycle Dataset. |
| title_fullStr | Accuracy & loss curves of the DenseNet201-Infused Parallel SE-CNN for OpenRecycle Dataset. |
| title_full_unstemmed | Accuracy & loss curves of the DenseNet201-Infused Parallel SE-CNN for OpenRecycle Dataset. |
| title_short | Accuracy & loss curves of the DenseNet201-Infused Parallel SE-CNN for OpenRecycle Dataset. |
| title_sort | Accuracy & loss curves of the DenseNet201-Infused Parallel SE-CNN for OpenRecycle Dataset. |
| topic | Ecology Science Policy Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified translating theoretical advancements towards sustainable solutions three additional datasets smart cities progress recycling processes depend promoting environmental sustainability promising heightened efficiency model &# 8217 become increasingly vital restoring waste materials enhance waste diversity effective waste collection waste management practices adaptable waste classification waste data xlink "> work presents transparent decision tangible stride successful deployment study presents reducing pollution recent years precise solution paradigm shift original states irrelevant features integrated squeeze including capturing important ones ground implementation focus areas distinguishable features deep learning current context attention mechanism applied strategically accurately identifying |