# Mushroom Classification Model - JarviSpore
This repository contains **JarviSpore**, a mushroom image classification model trained on a multi-class dataset with 23 different types of mushrooms. Developed from scratch with TensorFlow and Keras, this model aims to provide accurate mushroom identification using advanced deep learning techniques, including *Grad-CAM* for interpreting predictions. This project explores the performance of from-scratch models compared to transfer learning.
## Model Details
- **Architecture**: Custom CNN (Convolutional Neural Network)
- **Number of Classes**: 23 mushroom classes
- **Input Format**: RGB images resized to 224x224 pixels
- **Framework**: TensorFlow & Keras
- **Training**: Conducted on a machine with an i9 14900k processor, 192GB RAM, and an RTX 3090 GPU
## Key Features
1. **Multi-Class Classification**: The model can predict among 23 mushroom species.
2. **Regularization**: Includes L2 regularization and Dropout to prevent overfitting.
3. *…
# Mushroom Classification Model - JarviSpore
This repository contains **JarviSpore**, a mushroom image classification model trained on a multi-class dataset with 23 different types of mushrooms. Developed from scratch with TensorFlow and Keras, this model aims to provide accurate mushroom identification using advanced deep learning techniques, including *Grad-CAM* for interpreting predictions. This project explores the performance of from-scratch models compared to transfer learning.
## Model Details
- **Architecture**: Custom CNN (Convolutional Neural Network)
- **Number of Classes**: 23 mushroom classes
- **Input Format**: RGB images resized to 224x224 pixels
- **Framework**: TensorFlow & Keras
- **Training**: Conducted on a machine with an i9 14900k processor, 192GB RAM, and an RTX 3090 GPU
## Key Features
1. **Multi-Class Classification**: The model can predict among 23 mushroom species.
2. **Regularization**: Includes L2 regularization and Dropout to prevent overfitting.
3. *…
# Mushroom Classification Model - JarviSpore
This repository contains **JarviSpore**, a mushroom image classification model trained on a multi-class dataset with 23 different types of mushrooms. Developed from scratch with TensorFlow and Keras, this model aims to provide accurate mushroom identification using advanced deep learning techniques, including *Grad-CAM* for interpreting predictions. This project explores the performance of from-scratch models compared to transfer learning.
## Model Details
- **Architecture**: Custom CNN (Convolutional Neural Network)
- **Number of Classes**: 23 mushroom classes
- **Input Format**: RGB images resized to 224x224 pixels
- **Framework**: TensorFlow & Keras
- **Training**: Conducted on a machine with an i9 14900k processor, 192GB RAM, and an RTX 3090 GPU
## Key Features
1. **Multi-Class Classification**: The model can predict among 23 mushroom species.
2. **Regularization**: Includes L2 regularization and Dropout to prevent overfitting.
3. *…
