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Beit Base Land Cover V0.1
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Beit Base Land Cover V0.1
Developed by dfurman
An image classification model based on the BEiT architecture, fine-tuned on an image folder dataset with an accuracy rate of 98.7%
Downloads 22
Release Time : 11/18/2022
Model Overview
This model is a fine-tuned version of the microsoft/beit-base-patch16-224-pt22k-ft22k pre-trained model for image classification tasks, excelling in recognizing various natural scene image categories.
Model Features
High-precision classification
Achieves an excellent accuracy rate of 98.7% on the evaluation set.
Transfer learning optimization
Fine-tuned based on the powerful BEiT pre-trained model, fully leveraging pre-trained knowledge.
Multi-scene adaptation
Demonstrated capability to recognize various scenes such as tree canopies, low vegetation, impervious surfaces, and water bodies.
Model Capabilities
Image classification
Natural scene recognition
Multi-category image differentiation
Use Cases
Environmental monitoring
Vegetation coverage analysis
Identify different vegetation types (e.g., tree canopies vs. low vegetation)
Accurately distinguishes different vegetation types
Water body identification
Detect water body regions in images
High-precision water body recognition
Urban planning
Surface feature analysis
Identify artificial structures such as impervious surfaces
Accurately classifies artificial surface features
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