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Mask2former Finetuned ER Mito LD5
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Mask2former Finetuned ER Mito LD5

Developed by Dnq2025
An image segmentation model fine-tuned on the Dnq2025/Mask2former_Pretrain dataset, based on the facebook/mask2former-swin-base-IN21k-ade-semantic model
Image Segmentation
Transformers
Open Source License:Other#Organelle Segmentation#High-precision Semantic Segmentation#Biomedical Imaging
Downloads 26
Release Time : 4/3/2025

Model Overview

This model is a variant of the Mask2Former architecture, specifically designed for image segmentation tasks, with potential applications in the field of biomedical imaging.

Model Features

Powerful Backbone Network Based on Swin Transformer
Uses Swin Transformer as the feature extractor, effectively capturing multi-scale features of images
Mask2Former Architecture
Employs the advanced Mask2Former architecture, specifically designed for image segmentation tasks
Fine-tuning
Fine-tuned on specific datasets, potentially optimized for image segmentation tasks in particular domains

Model Capabilities

Image Segmentation
Semantic Segmentation
Biomedical Image Analysis

Use Cases

Biomedical Image Analysis
Organelle Segmentation
Used for identifying and segmenting organelles in electron microscopy images
Tissue Image Analysis
Image segmentation and analysis of medical tissue samples
General Image Segmentation
Scene Understanding
Object segmentation and recognition in complex scenes
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