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Segformer B0 Finetuned Segments Sidewalk 2

Developed by thesisabc
A SegFormer semantic segmentation model fine-tuned on the Segments.ai sidewalk-semantic dataset, suitable for sidewalk scene analysis
Downloads 16
Release Time : 6/21/2023

Model Overview

This model is a Transformer-based semantic segmentation model specifically optimized for sidewalk scenes, capable of accurately identifying and segmenting different elements in sidewalks

Model Features

Efficient Transformer Architecture
Adopts hierarchical Transformer encoder and lightweight all-MLP decoder head, providing accurate segmentation results while maintaining efficiency
Sidewalk Scene Optimization
Specifically fine-tuned on the sidewalk-semantic dataset, with enhanced recognition capability for sidewalk scenes
Simple and Efficient Design
The model features a concise and efficient design suitable for practical deployment

Model Capabilities

Image semantic segmentation
Sidewalk element recognition
Scene understanding

Use Cases

Smart City
Sidewalk Condition Monitoring
Used for urban sidewalk maintenance and condition assessment
Can accurately identify different types of sidewalk elements and defects
Autonomous Driving
Pedestrian Path Recognition
Assists autonomous driving systems in identifying walkable pedestrian areas
Provides precise sidewalk segmentation results
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