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Google Vit Base Patch16 224 Cartoon Emotion Detection

Developed by jayanta
A fine-tuned cartoon image emotion classification model based on Google Vision Transformer (ViT) architecture, achieving 88% accuracy on the test set
Downloads 25
Release Time : 1/22/2023

Model Overview

This model is specifically designed to recognize emotions expressed in cartoon images, fine-tuned on a custom image dataset based on the ViT architecture

Model Features

High Accuracy Emotion Recognition
Achieves 88.07% accuracy and 87.83% F1 score on the test set
Based on ViT Architecture
Utilizes the Vision Transformer base model with excellent image feature extraction capabilities
End-to-End Training
The model learns features directly from raw pixels without complex preprocessing

Model Capabilities

Cartoon Image Classification
Emotion Recognition
Image Feature Extraction

Use Cases

Entertainment Applications
Cartoon Expression Analysis
Analyze the emotional state of cartoon character expressions
Can identify multiple basic emotions
Content Moderation
Children's Content Filtering
Identify emotional tendencies in cartoon content
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