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  1. PramaLLC_BEN2.json +70 -0
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+ {
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+ "bomFormat": "CycloneDX",
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+ "specVersion": "1.6",
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+ "serialNumber": "urn:uuid:de0e0092-ebc9-47bd-a87c-e9c6fa4bc604",
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+ "version": 1,
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+ "metadata": {
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+ "timestamp": "2025-10-23T16:22:55.869800+00:00",
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+ "component": {
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+ "type": "machine-learning-model",
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+ "bom-ref": "PramaLLC/BEN2-4905de38-3fae-5f7c-8678-e3aa26a22745",
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+ "licenses": [
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+ {
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+ "license": {
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+ "id": "MIT",
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+ "url": "https://spdx.org/licenses/MIT.html"
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+ }
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+ }
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+ ],
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+ "externalReferences": [
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+ {
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+ "url": "https://huggingface.co/PramaLLC/BEN2",
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+ "type": "documentation"
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+ }
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+ ],
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+ "modelCard": {
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+ "modelParameters": {
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+ "datasets": [],
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+ "task": "image-segmentation",
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+ "modelArchitecture": "PramaBEN_Base"
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+ },
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+ "properties": [
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+ {
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+ "name": "library_name",
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+ "value": "ben2"
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+ }
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+ ]
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+ },
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+ "name": "PramaLLC/BEN2",
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+ "authors": [
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+ {
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+ "name": "PramaLLC"
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+ }
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+ ],
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+ "description": "## Overview\nBEN2 (Background Erase Network) introduces a novel approach to foreground segmentation through its innovative Confidence Guided Matting (CGM) pipeline. The architecture employs a refiner network that targets and processes pixels where the base model exhibits lower confidence levels, resulting in more precise and reliable matting results. This model is built on BEN:\n[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/ben-using-confidence-guided-matting-for/dichotomous-image-segmentation-on-dis-vd)](https://paperswithcode.com/sota/dichotomous-image-segmentation-on-dis-vd?p=ben-using-confidence-guided-matting-for)\n\n\n\n",
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+ "tags": [
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+ "ben2",
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+ "onnx",
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+ "safetensors",
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+ "BEN2",
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+ "background-remove",
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+ "mask-generation",
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+ "Dichotomous image segmentation",
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+ "background remove",
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+ "foreground",
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+ "background",
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+ "remove background",
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+ "pytorch",
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+ "model_hub_mixin",
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+ "pytorch_model_hub_mixin",
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+ "background removal",
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+ "background-removal",
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+ "image-segmentation",
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+ "arxiv:2501.06230",
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+ "license:mit",
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+ "region:us"
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+ ]
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+ }
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+ },
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+ "components": []
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+ }