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Srivardhan369/
Tumor_detection_ML_Model

Name: Tumor_detection_ML_Model
Availability: InStock

brain-tumor-image-dataset-semantic-segmentation

apache-2.0

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Tumor Detection ML Model

Model Description

This model is designed to classify brain tumor images using a Convolutional Neural Network (CNN). It has been trained and fine-tuned on a labeled dataset of brain tumor MRI images.

Training Details

Framework: TensorFlow/Keras
Optimizer: Adam with a learning rate scheduler
Loss Function: Categorical Crossentropy
Data Augmentation: Includes rotation, width/height shift, zoom, and horizontal flipping.
Hyperparameter Tuning: Performed using Keras Tuner.

Metrics

The following metrics were used to evaluate the model's performance:

Accuracy: Measures the overall correctness of predictions.
F1 Score: Balances precision and recall.
Precision: Indicates the proportion of true positives among positive predictions.
Recall: Indicates the proportion of true positives among all actual positives.

Usage

You can load the model using the Hugging Face Transformers library:

python

from transformers import AutoModel
model = AutoModel.from_pretrained("YourUsername/Tumor_detection_ML_Model")

Srivardhan369/Tumor_detection_ML_Model