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Convnext Base Land Cover V0.1
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Convnext Base Land Cover V0.1

Developed by dfurman
An image classification model fine-tuned based on the ConvNext-base architecture, excelling in land cover classification tasks with an accuracy of 99.19%.
Image Classification
Transformers
Open Source License:Apache-2.0#High-precision land cover classification#Fine-tuned ConvNext model#Remote sensing image recognition
Downloads 62
Release Time : 11/19/2022

Model Overview

This model is a fine-tuned version of facebook/convnext-base-224 on an image folder dataset, specifically designed for land cover classification tasks.

Model Features

High accuracy
Achieved an outstanding accuracy of 99.19% on the evaluation set.
Fine-tuning optimization
Fine-tuned based on the ConvNext-base architecture to adapt to land cover classification tasks.
Efficient training
Utilized mixed-precision training and the Adam optimizer for high training efficiency.

Model Capabilities

Image classification
Land cover identification
Canopy layer detection
Water body recognition
Impervious surface detection

Use Cases

Environmental monitoring
Forest cover analysis
Identify and classify canopy layer coverage
99.19% accuracy
Water body monitoring
Identify and classify water body extents
99.19% accuracy
Urban planning
Impervious surface detection
Identify impervious surfaces such as buildings and roads in urban areas
99.19% accuracy
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