Class-wise allocation of images in the FishSpecies Dataset.
<p>Class-wise allocation of images in the FishSpecies Dataset.</p>
محفوظ في:
| المؤلف الرئيسي: | |
|---|---|
| منشور في: |
2025
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| الموضوعات: | |
| الوسوم: |
إضافة وسم
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| _version_ | 1852020205132185600 |
|---|---|
| author | Ebru Ergün (21395498) |
| author_facet | Ebru Ergün (21395498) |
| author_role | author |
| dc.creator.none.fl_str_mv | Ebru Ergün (21395498) |
| dc.date.none.fl_str_mv | 2025-05-20T17:54:13Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0322711.t004 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/Class-wise_allocation_of_images_in_the_FishSpecies_Dataset_/29112950 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Ecology Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified matthews correlation coefficient hierarchical structure enhances edge architecture known confusion matrix metrics computer vision tasks 224 224 pixels deep learning models ca ), f1 global seafood trade div >< p optimizing market efficiency class fishspecies dataset improving food safety class smallfishbd dataset food safety fishspecies dataset market efficiency transfer learning seafood industry improving sustainability global features fish dataset class bd work offers unique ability tensor format swinfishnet ), swin transformer significant contributions results underscore research settings novel methodology model ’ innovative approach image processing fish market ensuring sustainability domestic economies crucial industry cohen ’ broad applications based classification based approach artificial intelligence applied using adamw algorithm |
| dc.title.none.fl_str_mv | Class-wise allocation of images in the FishSpecies Dataset. |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <p>Class-wise allocation of images in the FishSpecies Dataset.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_44edc3d81da7e44bdc8a05e8a749174a |
| identifier_str_mv | 10.1371/journal.pone.0322711.t004 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/29112950 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Class-wise allocation of images in the FishSpecies Dataset.Ebru Ergün (21395498)EcologySpace ScienceEnvironmental Sciences not elsewhere classifiedBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedmatthews correlation coefficienthierarchical structure enhancesedge architecture knownconfusion matrix metricscomputer vision tasks224 224 pixelsdeep learning modelsca ), f1global seafood tradediv >< poptimizing market efficiencyclass fishspecies datasetimproving food safetyclass smallfishbd datasetfood safetyfishspecies datasetmarket efficiencytransfer learningseafood industryimproving sustainabilityglobal featuresfish datasetclass bdwork offersunique abilitytensor formatswinfishnet ),swin transformersignificant contributionsresults underscoreresearch settingsnovel methodologymodel ’innovative approachimage processingfish marketensuring sustainabilitydomestic economiescrucial industrycohen ’broad applicationsbased classificationbased approachartificial intelligenceapplied usingadamw algorithm<p>Class-wise allocation of images in the FishSpecies Dataset.</p>2025-05-20T17:54:13ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0322711.t004https://figshare.com/articles/dataset/Class-wise_allocation_of_images_in_the_FishSpecies_Dataset_/29112950CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/291129502025-05-20T17:54:13Z |
| spellingShingle | Class-wise allocation of images in the FishSpecies Dataset. Ebru Ergün (21395498) Ecology Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified matthews correlation coefficient hierarchical structure enhances edge architecture known confusion matrix metrics computer vision tasks 224 224 pixels deep learning models ca ), f1 global seafood trade div >< p optimizing market efficiency class fishspecies dataset improving food safety class smallfishbd dataset food safety fishspecies dataset market efficiency transfer learning seafood industry improving sustainability global features fish dataset class bd work offers unique ability tensor format swinfishnet ), swin transformer significant contributions results underscore research settings novel methodology model ’ innovative approach image processing fish market ensuring sustainability domestic economies crucial industry cohen ’ broad applications based classification based approach artificial intelligence applied using adamw algorithm |
| status_str | publishedVersion |
| title | Class-wise allocation of images in the FishSpecies Dataset. |
| title_full | Class-wise allocation of images in the FishSpecies Dataset. |
| title_fullStr | Class-wise allocation of images in the FishSpecies Dataset. |
| title_full_unstemmed | Class-wise allocation of images in the FishSpecies Dataset. |
| title_short | Class-wise allocation of images in the FishSpecies Dataset. |
| title_sort | Class-wise allocation of images in the FishSpecies Dataset. |
| topic | Ecology Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified matthews correlation coefficient hierarchical structure enhances edge architecture known confusion matrix metrics computer vision tasks 224 224 pixels deep learning models ca ), f1 global seafood trade div >< p optimizing market efficiency class fishspecies dataset improving food safety class smallfishbd dataset food safety fishspecies dataset market efficiency transfer learning seafood industry improving sustainability global features fish dataset class bd work offers unique ability tensor format swinfishnet ), swin transformer significant contributions results underscore research settings novel methodology model ’ innovative approach image processing fish market ensuring sustainability domestic economies crucial industry cohen ’ broad applications based classification based approach artificial intelligence applied using adamw algorithm |