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Segments Sidewalk SegFormer B0

Developed by ayoubkirouane
Semantic segmentation model based on SegFormer-b0 architecture, specialized for sidewalk image analysis
Downloads 42
Release Time : 9/24/2023

Model Overview

This model is fine-tuned on the sidewalk-semantic dataset and can perform pixel-level classification of sidewalk images, identifying objects such as pavement, pedestrians, and vehicles

Model Features

Efficient Semantic Segmentation
Utilizes lightweight SegFormer architecture to achieve efficient inference while maintaining accuracy
Sidewalk Scene Optimization
Specially optimized for sidewalk scenes, accurately identifying key elements like pavement and pedestrians
Hierarchical Feature Extraction
Captures multi-scale features through a hierarchical Transformer encoder

Model Capabilities

Pixel-level image classification
Sidewalk element recognition
Scene understanding

Use Cases

Urban Management
Infrastructure Analysis
Automatically identifies and assesses sidewalk infrastructure conditions
Improves urban maintenance efficiency
Autonomous Driving
Environmental Perception
Provides sidewalk environment understanding for autonomous driving systems
Enhances navigation safety
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