Roadwork Detection Model
Model Details
Model Description
This is a Vision Transformer (ViT) model trained to detect roadwork in traffic images. The model can classify images into three categories: Roadwork Type A (normal/minimal), Roadwork Type B (significant), and Non-Roadwork. It provides binary output for miner tasks in blockchain networks.
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License: MIT
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Uses
Direct Use
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Bias, Risks, and Limitations
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Training Details
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Training Data
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Testing Data, Factors & Metrics
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Summary
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Model Examination
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Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator
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Technical Specifications
Model Architecture and Objective
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Compute Infrastructure
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Citation
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Glossary
- Roadwork Type A: [More Information Needed]
- Roadwork Type B: [More Information Needed]
- Non-Roadwork: [More Information Needed]
- Binary Classification: [More Information Needed]
More Information
This model is designed for use in blockchain mining applications where miners are rewarded based on their accuracy in detecting roadwork in traffic images. The model provides both detailed classification and binary output suitable for different use cases.
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Evaluation results
- Accuracy on Roadwork Detection Datasetself-reported0.850
- F1 Score on Roadwork Detection Datasetself-reported0.830