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Vit Base Patch16 224 In21k Plant Seedling Classification
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Vit Base Patch16 224 In21k Plant Seedling Classification

Developed by uisikdag
This is an image classification model fine-tuned based on google/vit-base-patch16-224-in21k, specifically designed for plant seedling classification tasks, achieving 95.67% accuracy on the test set.
Image Classification
Transformers
Open Source License:Apache-2.0#Plant seedling classification#High accuracy (95.67%)#ViT fine-tuned model
Downloads 40
Release Time : 3/8/2023

Model Overview

This model is a Vision Transformer trained on a balanced dataset, primarily used for plant seedling classification tasks. Images are resized to 224x224 and perform excellently on the test set.

Model Features

High accuracy
Achieves 95.67% classification accuracy on the test set, demonstrating excellent performance.
Based on ViT architecture
Uses the Vision Transformer base architecture with powerful feature extraction capabilities.
Balanced dataset training
Trained with 250 images per class to ensure fair learning across all categories.

Model Capabilities

Plant seedling image classification
Multi-category image recognition

Use Cases

Agriculture
Weed identification
Identify weed species in farmland
Helps farmers accurately remove weeds and improve crop yield.
Plant seedling classification
Classify different types of plant seedlings
Can be used for agricultural research and plant growth monitoring.
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