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Swin Base Patch4 Window7 224 In22k Plant Seedling Classification
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Swin Base Patch4 Window7 224 In22k Plant Seedling Classification

Developed by uisikdag
An image classification model based on Swin Transformer architecture, fine-tuned on an image folder dataset with an accuracy of 96.67%
Image Classification
Transformers
Open Source License:Apache-2.0#High-precision image classification#Agricultural weed recognition#Swin Transformer fine-tuning
Downloads 16
Release Time : 3/10/2023

Model Overview

This model is an image classification model fine-tuned from microsoft/swin-base-patch4-window7-224-in22k, primarily used for plant weed recognition tasks.

Model Features

High accuracy
Achieves 96.67% classification accuracy on the test set
Based on Swin Transformer
Utilizes advanced vision Transformer architecture with powerful feature extraction capabilities
Few-shot learning
Achieves excellent performance with fine-tuning on relatively small datasets

Model Capabilities

Image classification
Plant recognition
Weed detection

Use Cases

Agriculture
Automatic weed recognition
Used for automatic detection and classification of weeds in farmland
Accurately identifies different types of weeds with 96.67% accuracy
Plant research
Plant species classification
Assists botanists in plant species identification and research
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