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AMAES Resenc B Fomo260k

This repository contains the checkpoint of the model from the FOMO260K paper.

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Dateigröße
1,09 GB
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vRevision dcff5df
Aktualisiert
16. Sept. 2026
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Hugging Face

Quellenbeschreibung

ResEnc UNet pretrained on FOMO260K using AMAES

This repository contains the checkpoint of the model from the FOMO260K paper.

Finetuning the model for Segmentation tasks

To finetune the model with the configs used in the paper, simply use the following command

asp_finetune_seg \
    --config-name projects/datapaper/finetune/resenc_[dataset]_fewshot.yaml \
    checkpoint_path=path/to/checkpoint.ckpt

where [dataset] is one of {cerebrum, wmh, isles, atlas, sbm}.

Installing Asparagus

For instructions on how to install asparagus, preprocess your data, and make your own configs, please refer to the Asparagus Readme.

Quellen

1 Quelle
Hugging FacePrimärVersion dcff5df869541064e1c2834a4afb2d675e2ee03c
huggingface.co/FOMO-MRI/AMAES_resenc_b_fomo260k/tree/dcff5df869541064e1c2834a4afb2d675e2ee03c

Verifiziert 1. Sept.

Modellartefakte

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resenc_unet_b.ckpt

ckpt · 1,09 GB · SHA-256 115d509241ad…7749 · Hugging Face

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--- license: cc-by-nc-sa-4.0 datasets: - FOMO-MRI/FOMO260K pipeline_tag: image-segmentation --- # ResEnc UNet pretrained on FOMO260K using AMAES This repository contains the checkpoint of the model from the [FOMO260K paper](https://arxiv.org/abs/2506.14432). * Network: Resenc Unet B with 102M parameters ([model definition](https://github.com/Sllambias/asparagus/blob/72f333b9b59cf9c2a5689995b72a06d689707fec/asparagus/modules/networks/resenc_unet.py#L119)) * Pretext Task: [AMAES](https://arxiv.org/abs/2408.00640). * Dataset: [FOMO260K](https://huggingface.co/datasets/FOMO-MRI/FOMO260K). * Code: [Asparagus](https://github.com/Sllambias/asparagus). ## Finetuning the model for Segmentation tasks To finetune the model with the configs used in the paper, simply use the following command ``` asp_finetune_seg \ --config-name projects/datapaper/finetune/resenc_[dataset]_fewshot.yaml \ checkpoint_path=path/to/checkpoint.ckpt ``` where `[dataset]` is one of `{cerebrum, wmh, isles, atlas, sbm}`. ## Installing Asparagus For instructions on how to install asparagus, preprocess your data, and make your own configs, please refer to the [Asparagus Readme](https://github.com/Sllambias/asparagus).

Source context: 0 downloads · 0 likes · Pipeline image-segmentation · Repo FOMO-MRI/AMAES_resenc_b_fomo260k