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Segformer B4 City Satellite Segmentation 1024x1024
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Segformer B4 City Satellite Segmentation 1024x1024

Developed by ratnaonline1
A satellite image segmentation model based on the SegFormer architecture, specifically designed for urban area segmentation tasks
Image Segmentation
Transformers
Open Source License:Openrail#Satellite Image Segmentation#Urban Planning Analysis#High-Resolution Processing
Downloads 110
Release Time : 9/6/2023

Model Overview

This model uses the SegFormer-b4 architecture for semantic segmentation of urban satellite images at 1024x1024 resolution, capable of identifying different urban areas and land cover types

Model Features

High-Resolution Processing Capability
Supports direct input and processing of high-resolution satellite images at 1024x1024
Urban Area Segmentation
Specifically designed for precise segmentation of various land covers and areas in urban environments
SegFormer Architecture
Utilizes the efficient SegFormer-b4 architecture, balancing performance and computational efficiency

Model Capabilities

Satellite Image Analysis
Urban Area Recognition
Semantic Segmentation
High-Resolution Image Processing

Use Cases

Urban Planning
Urban Land Use Analysis
Identifies different functional areas in cities such as residential zones, commercial districts, and green spaces
Provides accurate land use classification maps
Environmental Monitoring
Urban Green Coverage Calculation
Identifies and quantifies green areas in urban environments
Provides data support for urban environmental assessments
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