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{
            
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  "access_rights": "",
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  "access_rights": "",
            
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  "author": "Leander Lauenburg",
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  "author": "Leander Lauenburg",
            
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  "author_email": "",
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  "author_email": "",
            
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  "citation": [],
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  "citation": [],
            
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  "defined_in": "",
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  "doi": "10.57702/r21dylur",
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  "doi": "10.57702/r21dylur",
            
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  "doi_date_published": null,
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  "doi_date_published": "2024-12-02",
            
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  "doi_publisher": "TIB",
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  "doi_publisher": "TIB",
            
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  "domain": "https://service.tib.eu/ldmservice",
            
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  "extra_authors": [
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  "extra_authors": [
            
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    {
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    {
            
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      "extra_author": "Zudi Lin",
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      "extra_author": "Zudi Lin",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Ruihan Zhang",
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      "extra_author": "Ruihan Zhang",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "M\u00b4arcia dos Santos",
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      "extra_author": "M\u00b4arcia dos Santos",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Siyu Huang",
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      "extra_author": "Siyu Huang",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Ignacio Arganda-Carreras",
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      "extra_author": "Ignacio Arganda-Carreras",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Edward S. Boyden",
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      "extra_author": "Edward S. Boyden",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Hanspeter P\ufb01ster",
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      "extra_author": "Hanspeter P\ufb01ster",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Donglai Wei",
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      "extra_author": "Donglai Wei",
            
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      "orcid": ""
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      "orcid": ""
            
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    }
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    }
            
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  ],
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    {
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    {
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Instance Segmentation",
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      "display_name": "Instance Segmentation",
            
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      "name": "instance-segmentation",
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      "name": "instance-segmentation",
            
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      "title": "Instance Segmentation"
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      "title": "Instance Segmentation"
            
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    },
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    },
            
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    {
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    {
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Unlabeled Modalities",
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      "display_name": "Unlabeled Modalities",
            
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      "name": "unlabeled-modalities",
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      "name": "unlabeled-modalities",
            
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      "title": "Unlabeled Modalities"
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      "title": "Unlabeled Modalities"
            
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    }
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  ],
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  "landing_page": 
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  "landing_page": 
            
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"https://connectomics-bazaar.github.io/proj/CySGAN/index.html",
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"https://connectomics-bazaar.github.io/proj/CySGAN/index.html",
            
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  "license_title": null,
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  "link_orkg": "",
            
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  "metadata_created": "2024-12-02T22:52:11.445558",
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  "metadata_created": "2024-12-02T22:52:11.445558",
            
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  "metadata_modified": "2024-12-02T22:52:12.196383",
            
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  "name": 
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  "name": 
            
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"cysgan--cyclic-segmentation-generative-adversarial-network",
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"cysgan--cyclic-segmentation-generative-adversarial-network",
            
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  "notes": "Instance segmentation for unlabeled imaging modalities is 
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  "notes": "Instance segmentation for unlabeled imaging modalities is 
            
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a challenging but essential task as collecting expert annotation can 
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a challenging but essential task as collecting expert annotation can 
            
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be expensive and time-consuming. Existing works segment a new modality 
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be expensive and time-consuming. Existing works segment a new modality 
            
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by either deploying a pre-trained model optimized on diverse training 
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by either deploying a pre-trained model optimized on diverse training 
            
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data or conducting domain translation and image segmentation as two 
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data or conducting domain translation and image segmentation as two 
            
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independent steps.",
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independent steps.",
            
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    "approval_status": "approved",
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    "approval_status": "approved",
            
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      "created": "2024-12-02T22:29:38",
            
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      "description": "The json representation of the dataset with its 
            
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distributions based on DCAT.",
            
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      "format": "JSON",
            
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  "tags": [
            
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      "display_name": "Cyclic Segmentation",
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      "display_name": "Cyclic Segmentation",
            
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      "id": "651d6dec-48c5-40c5-a792-55128c85a907",
            
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      "name": "Cyclic Segmentation",
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      "name": "Cyclic Segmentation",
            
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      "name": "Generative Adversarial Network",
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      "name": "Generative Adversarial Network",
            
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      "state": "active",
            
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    {
            
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      "display_name": "Instance Segmentation",
            
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      "id": "b58d8dfe-1216-401d-8a2a-ceb09e07a013",
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      "id": "b58d8dfe-1216-401d-8a2a-ceb09e07a013",
            
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      "name": "Instance Segmentation",
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      "name": "Instance Segmentation",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "Unlabeled Modalities",
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      "display_name": "Unlabeled Modalities",
            
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      "id": "057b95bc-3889-42c7-b8d5-71d48bc96a77",
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      "id": "057b95bc-3889-42c7-b8d5-71d48bc96a77",
            
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      "name": "Unlabeled Modalities",
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      "name": "Unlabeled Modalities",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    }
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    }
            
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  ],
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  ],
            
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  "title": "CySGAN: Cyclic Segmentation Generative Adversarial 
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  "title": "CySGAN: Cyclic Segmentation Generative Adversarial 
            
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Network",
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Network",
            
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  "type": "dataset",
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  "type": "dataset",
            
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  "version": ""
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  "version": ""
            
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}
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}