Fine-tuning on same-model feature matching tasks. The X-FFN and Y-FFN represent the assistants of any two kinds of pre-trained different modal images in the second stage of Fig 4. The fine-tuning of the X-modal image and the fine-tuning of the Y-modal image are independent of each other.
<p>Fine-tuning on same-model feature matching tasks. The X-FFN and Y-FFN represent the assistants of any two kinds of pre-trained different modal images in the second stage of Fig 4. The fine-tuning of the X-modal image and the fine-tuning of the Y-modal image are independent of each other.<...
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2025
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| _version_ | 1852021690906705920 |
|---|---|
| author | Yide Di (20969124) |
| author2 | Yun Liao (160524) Hao Zhou (136535) Kaijun Zhu (18283913) Qing Duan (541846) Junhui Liu (2063140) Mingyu Lu (2333083) |
| author2_role | author author author author author author |
| author_facet | Yide Di (20969124) Yun Liao (160524) Hao Zhou (136535) Kaijun Zhu (18283913) Qing Duan (541846) Junhui Liu (2063140) Mingyu Lu (2333083) |
| author_role | author |
| dc.creator.none.fl_str_mv | Yide Di (20969124) Yun Liao (160524) Hao Zhou (136535) Kaijun Zhu (18283913) Qing Duan (541846) Junhui Liu (2063140) Mingyu Lu (2333083) |
| dc.date.none.fl_str_mv | 2025-03-31T20:05:25Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0319051.g005 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Fine-tuning_on_same-model_feature_matching_tasks_The_X-FFN_and_Y-FFN_represent_the_assistants_of_any_two_kinds_of_pre-trained_different_modal_images_in_the_second_stage_of_Fig_4_The_fine-tuning_of_the_X-modal_image_and_the_fine-tuning_of_th/28701039 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Sociology Science Policy Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified multimodal image applications image feature matching experimental results demonstrate data augmentation algorithm across different modals ufm exhibits versatility div >< p imbalanced modal datasets specific modals specific datasets sparse data wide spectrum ufm excels ufm </ trained model staged pre remains challenging modal images foundational task computer vision |
| dc.title.none.fl_str_mv | Fine-tuning on same-model feature matching tasks. The X-FFN and Y-FFN represent the assistants of any two kinds of pre-trained different modal images in the second stage of Fig 4. The fine-tuning of the X-modal image and the fine-tuning of the Y-modal image are independent of each other. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>Fine-tuning on same-model feature matching tasks. The X-FFN and Y-FFN represent the assistants of any two kinds of pre-trained different modal images in the second stage of Fig 4. The fine-tuning of the X-modal image and the fine-tuning of the Y-modal image are independent of each other.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_c85d9fb8fdf8167ec4cd16cad454e521 |
| identifier_str_mv | 10.1371/journal.pone.0319051.g005 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/28701039 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Fine-tuning on same-model feature matching tasks. The X-FFN and Y-FFN represent the assistants of any two kinds of pre-trained different modal images in the second stage of Fig 4. The fine-tuning of the X-modal image and the fine-tuning of the Y-modal image are independent of each other.Yide Di (20969124)Yun Liao (160524)Hao Zhou (136535)Kaijun Zhu (18283913)Qing Duan (541846)Junhui Liu (2063140)Mingyu Lu (2333083)SociologyScience PolicySpace ScienceBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedmultimodal image applicationsimage feature matchingexperimental results demonstratedata augmentation algorithmacross different modalsufm exhibits versatilitydiv >< pimbalanced modal datasetsspecific modalsspecific datasetssparse datawide spectrumufm excelsufm </trained modelstaged preremains challengingmodal imagesfoundational taskcomputer vision<p>Fine-tuning on same-model feature matching tasks. The X-FFN and Y-FFN represent the assistants of any two kinds of pre-trained different modal images in the second stage of Fig 4. The fine-tuning of the X-modal image and the fine-tuning of the Y-modal image are independent of each other.</p>2025-03-31T20:05:25ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0319051.g005https://figshare.com/articles/figure/Fine-tuning_on_same-model_feature_matching_tasks_The_X-FFN_and_Y-FFN_represent_the_assistants_of_any_two_kinds_of_pre-trained_different_modal_images_in_the_second_stage_of_Fig_4_The_fine-tuning_of_the_X-modal_image_and_the_fine-tuning_of_th/28701039CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/287010392025-03-31T20:05:25Z |
| spellingShingle | Fine-tuning on same-model feature matching tasks. The X-FFN and Y-FFN represent the assistants of any two kinds of pre-trained different modal images in the second stage of Fig 4. The fine-tuning of the X-modal image and the fine-tuning of the Y-modal image are independent of each other. Yide Di (20969124) Sociology Science Policy Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified multimodal image applications image feature matching experimental results demonstrate data augmentation algorithm across different modals ufm exhibits versatility div >< p imbalanced modal datasets specific modals specific datasets sparse data wide spectrum ufm excels ufm </ trained model staged pre remains challenging modal images foundational task computer vision |
| status_str | publishedVersion |
| title | Fine-tuning on same-model feature matching tasks. The X-FFN and Y-FFN represent the assistants of any two kinds of pre-trained different modal images in the second stage of Fig 4. The fine-tuning of the X-modal image and the fine-tuning of the Y-modal image are independent of each other. |
| title_full | Fine-tuning on same-model feature matching tasks. The X-FFN and Y-FFN represent the assistants of any two kinds of pre-trained different modal images in the second stage of Fig 4. The fine-tuning of the X-modal image and the fine-tuning of the Y-modal image are independent of each other. |
| title_fullStr | Fine-tuning on same-model feature matching tasks. The X-FFN and Y-FFN represent the assistants of any two kinds of pre-trained different modal images in the second stage of Fig 4. The fine-tuning of the X-modal image and the fine-tuning of the Y-modal image are independent of each other. |
| title_full_unstemmed | Fine-tuning on same-model feature matching tasks. The X-FFN and Y-FFN represent the assistants of any two kinds of pre-trained different modal images in the second stage of Fig 4. The fine-tuning of the X-modal image and the fine-tuning of the Y-modal image are independent of each other. |
| title_short | Fine-tuning on same-model feature matching tasks. The X-FFN and Y-FFN represent the assistants of any two kinds of pre-trained different modal images in the second stage of Fig 4. The fine-tuning of the X-modal image and the fine-tuning of the Y-modal image are independent of each other. |
| title_sort | Fine-tuning on same-model feature matching tasks. The X-FFN and Y-FFN represent the assistants of any two kinds of pre-trained different modal images in the second stage of Fig 4. The fine-tuning of the X-modal image and the fine-tuning of the Y-modal image are independent of each other. |
| topic | Sociology Science Policy Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified multimodal image applications image feature matching experimental results demonstrate data augmentation algorithm across different modals ufm exhibits versatility div >< p imbalanced modal datasets specific modals specific datasets sparse data wide spectrum ufm excels ufm </ trained model staged pre remains challenging modal images foundational task computer vision |