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Vision Transformer Fmri Classification Ft
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Vision Transformer Fmri Classification Ft

Developed by shivkumarganesh
fMRI image classification model based on Vision Transformer architecture, automatically generated by HuggingPics
Image Classification
Transformers
#fMRI image classification#ViT architecture#Medical image analysis
Downloads 82
Release Time : 3/2/2022

Model Overview

This model is a Vision Transformer for fMRI (functional magnetic resonance imaging) image classification, fine-tuned for specific classification tasks.

Model Features

Based on Vision Transformer architecture
Utilizes Transformer architecture for processing image data, suitable for high-dimensional medical images like fMRI
High accuracy
Achieves approximately 79.56% classification accuracy on test sets
Easy to fine-tune
Can easily create and fine-tune your own image classifier using HuggingPics tools

Model Capabilities

fMRI image classification
Medical image analysis
Transformer-based visual processing

Use Cases

Medical image analysis
Brain functional state classification
Classify brain functional states through fMRI images
Approximately 79.56% accuracy
Neuroscience research
Cognitive state recognition
Identify brain activity patterns when subjects perform different cognitive tasks
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